Ben Bolstad
| Snapshot Date: 2025-11-20 13:40 -0500 (Thu, 20 Nov 2025) |
| 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 2025-11-21 11:39 -0500 (Fri, 21 Nov 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 24.04.3 LTS) | x86_64 | R Under development (unstable) (2025-10-20 r88955) -- "Unsuffered Consequences" | 4829 |
| lconway | macOS 12.7.6 Monterey | x86_64 | R Under development (unstable) (2025-10-21 r88958) -- "Unsuffered Consequences" | 4602 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | R Under development (unstable) (2025-11-04 r88984) -- "Unsuffered Consequences" | 4566 |
| 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 252/2327 | 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 | | ||||||||
| lconway | macOS 12.7.6 Monterey / x86_64 | OK | OK | WARNINGS | 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: 2025-11-20 18:49:48 -0500 (Thu, 20 Nov 2025) |
| EndedAt: 2025-11-20 18:50:09 -0500 (Thu, 20 Nov 2025) |
| 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
0.145 0.056 0.197
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 Nov 20 18:50:00 2025"
> 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 Nov 20 18:50:00 2025"
>
>
> 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: 0x6000000d80c0>
>
>
>
> 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 Nov 20 18:50:01 2025"
> 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 Nov 20 18:50:02 2025"
>
> ColMode(tmp2)
<pointer: 0x6000000d80c0>
>
>
>
> ### 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,] 101.5149352 -2.6295118 1.5006137 -0.3702499
[2,] 1.1552962 -0.4628999 0.7634099 2.1158279
[3,] 0.3674865 -0.5169299 -0.6371168 0.9104944
[4,] 0.3797454 -1.2106196 -0.3594800 0.8248065
> 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,] 101.5149352 2.6295118 1.5006137 0.3702499
[2,] 1.1552962 0.4628999 0.7634099 2.1158279
[3,] 0.3674865 0.5169299 0.6371168 0.9104944
[4,] 0.3797454 1.2106196 0.3594800 0.8248065
> 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,] 10.0754620 1.6215770 1.2249954 0.6084816
[2,] 1.0748471 0.6803675 0.8737333 1.4545886
[3,] 0.6062067 0.7189784 0.7981960 0.9541983
[4,] 0.6162348 1.1002816 0.5995665 0.9081886
>
> 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,] 227.26956 43.84528 38.75057 31.45507
[2,] 36.90377 32.26657 34.50074 41.66171
[3,] 31.42955 32.70671 33.61908 35.45248
[4,] 31.54209 37.21344 31.35514 34.90669
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x6000000f8000>
> exp(tmp5)
<pointer: 0x6000000f8000>
> log(tmp5,2)
<pointer: 0x6000000f8000>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 473.0318
> Min(tmp5)
[1] 52.11369
> mean(tmp5)
[1] 73.21999
> Sum(tmp5)
[1] 14644
> Var(tmp5)
[1] 881.4995
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 91.29783 71.33888 73.78516 70.73928 69.02245 68.95031 72.29654 70.94542
[9] 71.96592 71.85815
> rowSums(tmp5)
[1] 1825.957 1426.778 1475.703 1414.786 1380.449 1379.006 1445.931 1418.908
[9] 1439.318 1437.163
> rowVars(tmp5)
[1] 8163.32824 58.51129 48.43534 89.90536 87.63443 67.25782
[7] 122.20352 55.22639 66.48370 71.32617
> rowSd(tmp5)
[1] 90.351139 7.649267 6.959550 9.481844 9.361326 8.201087 11.054570
[8] 7.431446 8.153754 8.445482
> rowMax(tmp5)
[1] 473.03180 86.71340 91.25483 86.63287 84.97935 85.79712 95.46568
[8] 85.60500 85.95604 83.78188
> rowMin(tmp5)
[1] 54.83838 60.96924 64.97636 52.11369 52.89317 57.19488 55.65000 58.41473
[9] 55.72162 54.58087
>
> colMeans(tmp5)
[1] 111.99960 69.88182 72.64377 73.83917 75.42578 68.04517 70.37275
[8] 75.92687 70.94059 70.26249 67.78739 68.68913 74.41844 76.01788
[15] 72.06378 69.56969 68.93476 69.07006 66.96844 71.54228
> colSums(tmp5)
[1] 1119.9960 698.8182 726.4377 738.3917 754.2578 680.4517 703.7275
[8] 759.2687 709.4059 702.6249 677.8739 686.8913 744.1844 760.1788
[15] 720.6378 695.6969 689.3476 690.7006 669.6844 715.4228
> colVars(tmp5)
[1] 16179.23588 101.60246 66.61649 115.08151 95.70463 95.42273
[7] 59.89363 109.31783 84.71978 67.32438 32.50000 66.99724
[13] 54.23438 129.14100 63.01167 51.10516 55.26601 71.58641
[19] 43.51570 28.44905
> colSd(tmp5)
[1] 127.197625 10.079804 8.161892 10.727605 9.782874 9.768456
[7] 7.739097 10.455517 9.204335 8.205143 5.700877 8.185184
[13] 7.364400 11.364022 7.937989 7.148787 7.434111 8.460875
[19] 6.596643 5.333765
> colMax(tmp5)
[1] 473.03180 91.25821 85.60500 95.46568 87.12093 81.22044 82.11787
[8] 84.32475 84.53878 84.02948 76.82071 81.48268 84.47912 91.25483
[15] 86.63287 83.64103 77.85717 80.94752 81.93242 81.18259
> colMin(tmp5)
[1] 61.93722 57.67408 58.58500 63.32034 57.19488 52.89317 58.45401 55.72162
[9] 54.83838 54.58087 60.41830 57.55737 67.90416 52.11369 62.77107 60.96924
[17] 58.19622 58.41473 60.80452 61.50112
>
>
> ### 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] 91.29783 71.33888 73.78516 70.73928 69.02245 NA 72.29654 70.94542
[9] 71.96592 71.85815
> rowSums(tmp5)
[1] 1825.957 1426.778 1475.703 1414.786 1380.449 NA 1445.931 1418.908
[9] 1439.318 1437.163
> rowVars(tmp5)
[1] 8163.32824 58.51129 48.43534 89.90536 87.63443 69.85334
[7] 122.20352 55.22639 66.48370 71.32617
> rowSd(tmp5)
[1] 90.351139 7.649267 6.959550 9.481844 9.361326 8.357831 11.054570
[8] 7.431446 8.153754 8.445482
> rowMax(tmp5)
[1] 473.03180 86.71340 91.25483 86.63287 84.97935 NA 95.46568
[8] 85.60500 85.95604 83.78188
> rowMin(tmp5)
[1] 54.83838 60.96924 64.97636 52.11369 52.89317 NA 55.65000 58.41473
[9] 55.72162 54.58087
>
> colMeans(tmp5)
[1] 111.99960 69.88182 72.64377 73.83917 75.42578 68.04517 70.37275
[8] 75.92687 70.94059 70.26249 67.78739 68.68913 74.41844 76.01788
[15] 72.06378 69.56969 68.93476 69.07006 66.96844 NA
> colSums(tmp5)
[1] 1119.9960 698.8182 726.4377 738.3917 754.2578 680.4517 703.7275
[8] 759.2687 709.4059 702.6249 677.8739 686.8913 744.1844 760.1788
[15] 720.6378 695.6969 689.3476 690.7006 669.6844 NA
> colVars(tmp5)
[1] 16179.23588 101.60246 66.61649 115.08151 95.70463 95.42273
[7] 59.89363 109.31783 84.71978 67.32438 32.50000 66.99724
[13] 54.23438 129.14100 63.01167 51.10516 55.26601 71.58641
[19] 43.51570 NA
> colSd(tmp5)
[1] 127.197625 10.079804 8.161892 10.727605 9.782874 9.768456
[7] 7.739097 10.455517 9.204335 8.205143 5.700877 8.185184
[13] 7.364400 11.364022 7.937989 7.148787 7.434111 8.460875
[19] 6.596643 NA
> colMax(tmp5)
[1] 473.03180 91.25821 85.60500 95.46568 87.12093 81.22044 82.11787
[8] 84.32475 84.53878 84.02948 76.82071 81.48268 84.47912 91.25483
[15] 86.63287 83.64103 77.85717 80.94752 81.93242 NA
> colMin(tmp5)
[1] 61.93722 57.67408 58.58500 63.32034 57.19488 52.89317 58.45401 55.72162
[9] 54.83838 54.58087 60.41830 57.55737 67.90416 52.11369 62.77107 60.96924
[17] 58.19622 58.41473 60.80452 NA
>
> Max(tmp5,na.rm=TRUE)
[1] 473.0318
> Min(tmp5,na.rm=TRUE)
[1] 52.11369
> mean(tmp5,na.rm=TRUE)
[1] 73.21925
> Sum(tmp5,na.rm=TRUE)
[1] 14570.63
> Var(tmp5,na.rm=TRUE)
[1] 885.9514
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.29783 71.33888 73.78516 70.73928 69.02245 68.71782 72.29654 70.94542
[9] 71.96592 71.85815
> rowSums(tmp5,na.rm=TRUE)
[1] 1825.957 1426.778 1475.703 1414.786 1380.449 1305.639 1445.931 1418.908
[9] 1439.318 1437.163
> rowVars(tmp5,na.rm=TRUE)
[1] 8163.32824 58.51129 48.43534 89.90536 87.63443 69.85334
[7] 122.20352 55.22639 66.48370 71.32617
> rowSd(tmp5,na.rm=TRUE)
[1] 90.351139 7.649267 6.959550 9.481844 9.361326 8.357831 11.054570
[8] 7.431446 8.153754 8.445482
> rowMax(tmp5,na.rm=TRUE)
[1] 473.03180 86.71340 91.25483 86.63287 84.97935 85.79712 95.46568
[8] 85.60500 85.95604 83.78188
> rowMin(tmp5,na.rm=TRUE)
[1] 54.83838 60.96924 64.97636 52.11369 52.89317 57.19488 55.65000 58.41473
[9] 55.72162 54.58087
>
> colMeans(tmp5,na.rm=TRUE)
[1] 111.99960 69.88182 72.64377 73.83917 75.42578 68.04517 70.37275
[8] 75.92687 70.94059 70.26249 67.78739 68.68913 74.41844 76.01788
[15] 72.06378 69.56969 68.93476 69.07006 66.96844 71.33948
> colSums(tmp5,na.rm=TRUE)
[1] 1119.9960 698.8182 726.4377 738.3917 754.2578 680.4517 703.7275
[8] 759.2687 709.4059 702.6249 677.8739 686.8913 744.1844 760.1788
[15] 720.6378 695.6969 689.3476 690.7006 669.6844 642.0553
> colVars(tmp5,na.rm=TRUE)
[1] 16179.23588 101.60246 66.61649 115.08151 95.70463 95.42273
[7] 59.89363 109.31783 84.71978 67.32438 32.50000 66.99724
[13] 54.23438 129.14100 63.01167 51.10516 55.26601 71.58641
[19] 43.51570 31.54248
> colSd(tmp5,na.rm=TRUE)
[1] 127.197625 10.079804 8.161892 10.727605 9.782874 9.768456
[7] 7.739097 10.455517 9.204335 8.205143 5.700877 8.185184
[13] 7.364400 11.364022 7.937989 7.148787 7.434111 8.460875
[19] 6.596643 5.616270
> colMax(tmp5,na.rm=TRUE)
[1] 473.03180 91.25821 85.60500 95.46568 87.12093 81.22044 82.11787
[8] 84.32475 84.53878 84.02948 76.82071 81.48268 84.47912 91.25483
[15] 86.63287 83.64103 77.85717 80.94752 81.93242 81.18259
> colMin(tmp5,na.rm=TRUE)
[1] 61.93722 57.67408 58.58500 63.32034 57.19488 52.89317 58.45401 55.72162
[9] 54.83838 54.58087 60.41830 57.55737 67.90416 52.11369 62.77107 60.96924
[17] 58.19622 58.41473 60.80452 61.50112
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.29783 71.33888 73.78516 70.73928 69.02245 NaN 72.29654 70.94542
[9] 71.96592 71.85815
> rowSums(tmp5,na.rm=TRUE)
[1] 1825.957 1426.778 1475.703 1414.786 1380.449 0.000 1445.931 1418.908
[9] 1439.318 1437.163
> rowVars(tmp5,na.rm=TRUE)
[1] 8163.32824 58.51129 48.43534 89.90536 87.63443 NA
[7] 122.20352 55.22639 66.48370 71.32617
> rowSd(tmp5,na.rm=TRUE)
[1] 90.351139 7.649267 6.959550 9.481844 9.361326 NA 11.054570
[8] 7.431446 8.153754 8.445482
> rowMax(tmp5,na.rm=TRUE)
[1] 473.03180 86.71340 91.25483 86.63287 84.97935 NA 95.46568
[8] 85.60500 85.95604 83.78188
> rowMin(tmp5,na.rm=TRUE)
[1] 54.83838 60.96924 64.97636 52.11369 52.89317 NA 55.65000 58.41473
[9] 55.72162 54.58087
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 114.91099 68.91797 74.20586 74.77758 77.45143 68.00253 71.69706
[8] 75.70188 71.03768 70.24448 68.60617 68.72269 74.93247 76.41960
[15] 70.86147 69.81390 69.92770 68.73273 67.58439 NaN
> colSums(tmp5,na.rm=TRUE)
[1] 1034.1989 620.2617 667.8527 672.9982 697.0629 612.0228 645.2735
[8] 681.3170 639.3391 632.2003 617.4556 618.5042 674.3922 687.7764
[15] 637.7533 628.3251 629.3493 618.5946 608.2595 0.0000
> colVars(tmp5,na.rm=TRUE)
[1] 18106.28341 103.85142 47.49227 119.55973 61.50582 107.33011
[7] 47.65027 122.41308 95.20371 75.73627 29.02035 75.35922
[13] 58.04123 143.46810 54.62581 56.82235 51.08254 79.25452
[19] 44.68699 NA
> colSd(tmp5,na.rm=TRUE)
[1] 134.559591 10.190752 6.891464 10.934337 7.842565 10.360025
[7] 6.902918 11.064044 9.757239 8.702659 5.387054 8.680969
[13] 7.618480 11.977817 7.390928 7.538060 7.147205 8.902501
[19] 6.684832 NA
> colMax(tmp5,na.rm=TRUE)
[1] 473.03180 91.25821 85.60500 95.46568 87.12093 81.22044 82.11787
[8] 84.32475 84.53878 84.02948 76.82071 81.48268 84.47912 91.25483
[15] 86.63287 83.64103 77.85717 80.94752 81.93242 -Inf
> colMin(tmp5,na.rm=TRUE)
[1] 61.93722 57.67408 65.26163 63.32034 65.60075 52.89317 62.97123 55.72162
[9] 54.83838 54.58087 61.41214 57.55737 67.90416 52.11369 62.77107 60.96924
[17] 58.19622 58.41473 60.80452 Inf
>
>
>
>
> 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] 185.1189 192.9699 202.6973 267.9465 221.3232 224.8391 307.5763 284.3054
[9] 220.7933 233.8491
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 185.1189 192.9699 202.6973 267.9465 221.3232 224.8391 307.5763 284.3054
[9] 220.7933 233.8491
>
>
>
> 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 5.684342e-14 -2.273737e-13 -5.684342e-14 0.000000e+00
[6] 5.684342e-14 -1.136868e-13 8.526513e-14 5.684342e-14 2.842171e-14
[11] 1.136868e-13 0.000000e+00 1.136868e-13 1.421085e-14 -5.684342e-14
[16] 1.136868e-13 7.105427e-14 -1.136868e-13 -5.684342e-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)
+ }
6 11
3 8
5 10
10 13
7 17
6 2
3 12
2 13
7 12
2 17
2 2
10 9
2 2
9 14
10 10
3 13
4 18
10 8
7 12
5 8
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] 2.430624
> Min(tmp)
[1] -3.006532
> mean(tmp)
[1] -0.05130284
> Sum(tmp)
[1] -5.130284
> Var(tmp)
[1] 1.116696
>
> rowMeans(tmp)
[1] -0.05130284
> rowSums(tmp)
[1] -5.130284
> rowVars(tmp)
[1] 1.116696
> rowSd(tmp)
[1] 1.056738
> rowMax(tmp)
[1] 2.430624
> rowMin(tmp)
[1] -3.006532
>
> colMeans(tmp)
[1] -0.60808309 1.58288360 0.31651319 -0.21350843 -0.19546823 -0.60622758
[7] 0.37937745 -0.07566899 1.21141877 -0.65305002 -2.61651583 -0.98391128
[13] 0.30451568 -0.21785040 0.06276372 0.96214147 0.76904943 0.03966095
[19] -2.14141581 0.66506922 -0.14672351 -1.09741692 2.35334996 -1.74839194
[25] 1.27763702 -1.27450376 -1.41403296 0.24533920 0.10906322 1.17821773
[31] -1.69393843 -0.07448263 -1.53438169 0.40183143 0.86586873 0.63694547
[37] 0.49609819 -3.00653205 -0.52605273 0.78015172 -1.39724124 -0.55268870
[43] 1.72774682 -1.94123173 0.05734558 0.88992518 1.96473846 -0.96239653
[49] 1.07693179 -0.25059831 -0.48995189 0.40447307 -0.67548677 -1.61372120
[55] -0.82789899 -0.26393724 -0.59760085 1.70847133 1.20960919 -0.27594502
[61] 0.77310213 -0.36918484 0.55875595 -1.23851478 2.43062429 -0.41875765
[67] 1.40295654 0.18391039 0.83607118 1.25699530 -0.81563587 -0.36313102
[73] -0.22106104 0.34162060 0.04051822 -1.23825317 -1.04957601 0.34897637
[79] -0.30513253 -1.36109970 -0.72948344 0.93752139 -0.84491073 -0.91339490
[85] -0.30750421 -0.06760174 0.23491167 -0.62327812 -0.47785142 1.92131722
[91] 0.83055228 -0.22127193 -0.85874488 0.29497297 -0.08312788 1.03833615
[97] 0.14253502 -0.51743116 1.86342038 -0.54271796
> colSums(tmp)
[1] -0.60808309 1.58288360 0.31651319 -0.21350843 -0.19546823 -0.60622758
[7] 0.37937745 -0.07566899 1.21141877 -0.65305002 -2.61651583 -0.98391128
[13] 0.30451568 -0.21785040 0.06276372 0.96214147 0.76904943 0.03966095
[19] -2.14141581 0.66506922 -0.14672351 -1.09741692 2.35334996 -1.74839194
[25] 1.27763702 -1.27450376 -1.41403296 0.24533920 0.10906322 1.17821773
[31] -1.69393843 -0.07448263 -1.53438169 0.40183143 0.86586873 0.63694547
[37] 0.49609819 -3.00653205 -0.52605273 0.78015172 -1.39724124 -0.55268870
[43] 1.72774682 -1.94123173 0.05734558 0.88992518 1.96473846 -0.96239653
[49] 1.07693179 -0.25059831 -0.48995189 0.40447307 -0.67548677 -1.61372120
[55] -0.82789899 -0.26393724 -0.59760085 1.70847133 1.20960919 -0.27594502
[61] 0.77310213 -0.36918484 0.55875595 -1.23851478 2.43062429 -0.41875765
[67] 1.40295654 0.18391039 0.83607118 1.25699530 -0.81563587 -0.36313102
[73] -0.22106104 0.34162060 0.04051822 -1.23825317 -1.04957601 0.34897637
[79] -0.30513253 -1.36109970 -0.72948344 0.93752139 -0.84491073 -0.91339490
[85] -0.30750421 -0.06760174 0.23491167 -0.62327812 -0.47785142 1.92131722
[91] 0.83055228 -0.22127193 -0.85874488 0.29497297 -0.08312788 1.03833615
[97] 0.14253502 -0.51743116 1.86342038 -0.54271796
> 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] -0.60808309 1.58288360 0.31651319 -0.21350843 -0.19546823 -0.60622758
[7] 0.37937745 -0.07566899 1.21141877 -0.65305002 -2.61651583 -0.98391128
[13] 0.30451568 -0.21785040 0.06276372 0.96214147 0.76904943 0.03966095
[19] -2.14141581 0.66506922 -0.14672351 -1.09741692 2.35334996 -1.74839194
[25] 1.27763702 -1.27450376 -1.41403296 0.24533920 0.10906322 1.17821773
[31] -1.69393843 -0.07448263 -1.53438169 0.40183143 0.86586873 0.63694547
[37] 0.49609819 -3.00653205 -0.52605273 0.78015172 -1.39724124 -0.55268870
[43] 1.72774682 -1.94123173 0.05734558 0.88992518 1.96473846 -0.96239653
[49] 1.07693179 -0.25059831 -0.48995189 0.40447307 -0.67548677 -1.61372120
[55] -0.82789899 -0.26393724 -0.59760085 1.70847133 1.20960919 -0.27594502
[61] 0.77310213 -0.36918484 0.55875595 -1.23851478 2.43062429 -0.41875765
[67] 1.40295654 0.18391039 0.83607118 1.25699530 -0.81563587 -0.36313102
[73] -0.22106104 0.34162060 0.04051822 -1.23825317 -1.04957601 0.34897637
[79] -0.30513253 -1.36109970 -0.72948344 0.93752139 -0.84491073 -0.91339490
[85] -0.30750421 -0.06760174 0.23491167 -0.62327812 -0.47785142 1.92131722
[91] 0.83055228 -0.22127193 -0.85874488 0.29497297 -0.08312788 1.03833615
[97] 0.14253502 -0.51743116 1.86342038 -0.54271796
> colMin(tmp)
[1] -0.60808309 1.58288360 0.31651319 -0.21350843 -0.19546823 -0.60622758
[7] 0.37937745 -0.07566899 1.21141877 -0.65305002 -2.61651583 -0.98391128
[13] 0.30451568 -0.21785040 0.06276372 0.96214147 0.76904943 0.03966095
[19] -2.14141581 0.66506922 -0.14672351 -1.09741692 2.35334996 -1.74839194
[25] 1.27763702 -1.27450376 -1.41403296 0.24533920 0.10906322 1.17821773
[31] -1.69393843 -0.07448263 -1.53438169 0.40183143 0.86586873 0.63694547
[37] 0.49609819 -3.00653205 -0.52605273 0.78015172 -1.39724124 -0.55268870
[43] 1.72774682 -1.94123173 0.05734558 0.88992518 1.96473846 -0.96239653
[49] 1.07693179 -0.25059831 -0.48995189 0.40447307 -0.67548677 -1.61372120
[55] -0.82789899 -0.26393724 -0.59760085 1.70847133 1.20960919 -0.27594502
[61] 0.77310213 -0.36918484 0.55875595 -1.23851478 2.43062429 -0.41875765
[67] 1.40295654 0.18391039 0.83607118 1.25699530 -0.81563587 -0.36313102
[73] -0.22106104 0.34162060 0.04051822 -1.23825317 -1.04957601 0.34897637
[79] -0.30513253 -1.36109970 -0.72948344 0.93752139 -0.84491073 -0.91339490
[85] -0.30750421 -0.06760174 0.23491167 -0.62327812 -0.47785142 1.92131722
[91] 0.83055228 -0.22127193 -0.85874488 0.29497297 -0.08312788 1.03833615
[97] 0.14253502 -0.51743116 1.86342038 -0.54271796
> colMedians(tmp)
[1] -0.60808309 1.58288360 0.31651319 -0.21350843 -0.19546823 -0.60622758
[7] 0.37937745 -0.07566899 1.21141877 -0.65305002 -2.61651583 -0.98391128
[13] 0.30451568 -0.21785040 0.06276372 0.96214147 0.76904943 0.03966095
[19] -2.14141581 0.66506922 -0.14672351 -1.09741692 2.35334996 -1.74839194
[25] 1.27763702 -1.27450376 -1.41403296 0.24533920 0.10906322 1.17821773
[31] -1.69393843 -0.07448263 -1.53438169 0.40183143 0.86586873 0.63694547
[37] 0.49609819 -3.00653205 -0.52605273 0.78015172 -1.39724124 -0.55268870
[43] 1.72774682 -1.94123173 0.05734558 0.88992518 1.96473846 -0.96239653
[49] 1.07693179 -0.25059831 -0.48995189 0.40447307 -0.67548677 -1.61372120
[55] -0.82789899 -0.26393724 -0.59760085 1.70847133 1.20960919 -0.27594502
[61] 0.77310213 -0.36918484 0.55875595 -1.23851478 2.43062429 -0.41875765
[67] 1.40295654 0.18391039 0.83607118 1.25699530 -0.81563587 -0.36313102
[73] -0.22106104 0.34162060 0.04051822 -1.23825317 -1.04957601 0.34897637
[79] -0.30513253 -1.36109970 -0.72948344 0.93752139 -0.84491073 -0.91339490
[85] -0.30750421 -0.06760174 0.23491167 -0.62327812 -0.47785142 1.92131722
[91] 0.83055228 -0.22127193 -0.85874488 0.29497297 -0.08312788 1.03833615
[97] 0.14253502 -0.51743116 1.86342038 -0.54271796
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.6080831 1.582884 0.3165132 -0.2135084 -0.1954682 -0.6062276 0.3793774
[2,] -0.6080831 1.582884 0.3165132 -0.2135084 -0.1954682 -0.6062276 0.3793774
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.07566899 1.211419 -0.65305 -2.616516 -0.9839113 0.3045157 -0.2178504
[2,] -0.07566899 1.211419 -0.65305 -2.616516 -0.9839113 0.3045157 -0.2178504
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 0.06276372 0.9621415 0.7690494 0.03966095 -2.141416 0.6650692 -0.1467235
[2,] 0.06276372 0.9621415 0.7690494 0.03966095 -2.141416 0.6650692 -0.1467235
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -1.097417 2.35335 -1.748392 1.277637 -1.274504 -1.414033 0.2453392
[2,] -1.097417 2.35335 -1.748392 1.277637 -1.274504 -1.414033 0.2453392
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 0.1090632 1.178218 -1.693938 -0.07448263 -1.534382 0.4018314 0.8658687
[2,] 0.1090632 1.178218 -1.693938 -0.07448263 -1.534382 0.4018314 0.8658687
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 0.6369455 0.4960982 -3.006532 -0.5260527 0.7801517 -1.397241 -0.5526887
[2,] 0.6369455 0.4960982 -3.006532 -0.5260527 0.7801517 -1.397241 -0.5526887
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 1.727747 -1.941232 0.05734558 0.8899252 1.964738 -0.9623965 1.076932
[2,] 1.727747 -1.941232 0.05734558 0.8899252 1.964738 -0.9623965 1.076932
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -0.2505983 -0.4899519 0.4044731 -0.6754868 -1.613721 -0.827899 -0.2639372
[2,] -0.2505983 -0.4899519 0.4044731 -0.6754868 -1.613721 -0.827899 -0.2639372
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -0.5976009 1.708471 1.209609 -0.275945 0.7731021 -0.3691848 0.558756
[2,] -0.5976009 1.708471 1.209609 -0.275945 0.7731021 -0.3691848 0.558756
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -1.238515 2.430624 -0.4187577 1.402957 0.1839104 0.8360712 1.256995
[2,] -1.238515 2.430624 -0.4187577 1.402957 0.1839104 0.8360712 1.256995
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -0.8156359 -0.363131 -0.221061 0.3416206 0.04051822 -1.238253 -1.049576
[2,] -0.8156359 -0.363131 -0.221061 0.3416206 0.04051822 -1.238253 -1.049576
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 0.3489764 -0.3051325 -1.3611 -0.7294834 0.9375214 -0.8449107 -0.9133949
[2,] 0.3489764 -0.3051325 -1.3611 -0.7294834 0.9375214 -0.8449107 -0.9133949
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] -0.3075042 -0.06760174 0.2349117 -0.6232781 -0.4778514 1.921317 0.8305523
[2,] -0.3075042 -0.06760174 0.2349117 -0.6232781 -0.4778514 1.921317 0.8305523
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -0.2212719 -0.8587449 0.294973 -0.08312788 1.038336 0.142535 -0.5174312
[2,] -0.2212719 -0.8587449 0.294973 -0.08312788 1.038336 0.142535 -0.5174312
[,99] [,100]
[1,] 1.86342 -0.542718
[2,] 1.86342 -0.542718
>
>
> Max(tmp2)
[1] 2.649489
> Min(tmp2)
[1] -2.188321
> mean(tmp2)
[1] -0.04094756
> Sum(tmp2)
[1] -4.094756
> Var(tmp2)
[1] 0.962896
>
> rowMeans(tmp2)
[1] -0.38804718 0.63755340 1.24217871 -0.12764972 2.19192880 0.54020094
[7] -1.08212771 0.65573784 0.29661885 -0.75126420 1.08537909 -0.45443064
[13] -1.41041103 -1.04419373 -0.68941750 -0.32087463 -0.84707038 2.64948936
[19] 0.61037555 -0.21415764 2.16160844 0.58229184 -0.36350820 -0.57647170
[25] -1.29682389 -0.79990742 -0.12720781 1.10917212 -1.16109719 -1.18597162
[31] 2.04677461 -0.76518328 0.62699006 0.22345038 0.50235667 -0.46661063
[37] 0.69403217 -0.16520012 -0.71601839 -0.26158587 1.33119918 -0.47930048
[43] -0.94776481 -2.04683713 -0.32002821 -0.33239046 -1.04976704 1.32398341
[49] -1.47076073 -1.14920297 0.25743844 -0.28062017 -1.23841401 -1.29231020
[55] 0.30746282 -1.25683235 -0.94098062 1.65934725 1.02140703 0.00669940
[61] 0.31235021 1.43427683 -0.71091763 0.79646036 0.17397555 0.45575234
[67] 1.13441832 -0.09212644 -0.98045005 1.22923696 -1.03771539 -0.55447263
[73] -1.06134268 -0.57112095 -0.71234073 -0.04908166 -1.23712375 0.10076032
[79] 0.67872001 0.76436949 -1.03376427 -0.04494487 1.38133585 0.53080492
[85] 1.24791892 0.58648918 0.16861563 -0.29153601 1.08787337 -0.85388756
[91] -0.06359805 -0.68930507 0.39487417 0.96115206 -0.61883868 -2.18832142
[97] -1.40949664 0.33430459 -0.56712936 1.15583230
> rowSums(tmp2)
[1] -0.38804718 0.63755340 1.24217871 -0.12764972 2.19192880 0.54020094
[7] -1.08212771 0.65573784 0.29661885 -0.75126420 1.08537909 -0.45443064
[13] -1.41041103 -1.04419373 -0.68941750 -0.32087463 -0.84707038 2.64948936
[19] 0.61037555 -0.21415764 2.16160844 0.58229184 -0.36350820 -0.57647170
[25] -1.29682389 -0.79990742 -0.12720781 1.10917212 -1.16109719 -1.18597162
[31] 2.04677461 -0.76518328 0.62699006 0.22345038 0.50235667 -0.46661063
[37] 0.69403217 -0.16520012 -0.71601839 -0.26158587 1.33119918 -0.47930048
[43] -0.94776481 -2.04683713 -0.32002821 -0.33239046 -1.04976704 1.32398341
[49] -1.47076073 -1.14920297 0.25743844 -0.28062017 -1.23841401 -1.29231020
[55] 0.30746282 -1.25683235 -0.94098062 1.65934725 1.02140703 0.00669940
[61] 0.31235021 1.43427683 -0.71091763 0.79646036 0.17397555 0.45575234
[67] 1.13441832 -0.09212644 -0.98045005 1.22923696 -1.03771539 -0.55447263
[73] -1.06134268 -0.57112095 -0.71234073 -0.04908166 -1.23712375 0.10076032
[79] 0.67872001 0.76436949 -1.03376427 -0.04494487 1.38133585 0.53080492
[85] 1.24791892 0.58648918 0.16861563 -0.29153601 1.08787337 -0.85388756
[91] -0.06359805 -0.68930507 0.39487417 0.96115206 -0.61883868 -2.18832142
[97] -1.40949664 0.33430459 -0.56712936 1.15583230
> 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] -0.38804718 0.63755340 1.24217871 -0.12764972 2.19192880 0.54020094
[7] -1.08212771 0.65573784 0.29661885 -0.75126420 1.08537909 -0.45443064
[13] -1.41041103 -1.04419373 -0.68941750 -0.32087463 -0.84707038 2.64948936
[19] 0.61037555 -0.21415764 2.16160844 0.58229184 -0.36350820 -0.57647170
[25] -1.29682389 -0.79990742 -0.12720781 1.10917212 -1.16109719 -1.18597162
[31] 2.04677461 -0.76518328 0.62699006 0.22345038 0.50235667 -0.46661063
[37] 0.69403217 -0.16520012 -0.71601839 -0.26158587 1.33119918 -0.47930048
[43] -0.94776481 -2.04683713 -0.32002821 -0.33239046 -1.04976704 1.32398341
[49] -1.47076073 -1.14920297 0.25743844 -0.28062017 -1.23841401 -1.29231020
[55] 0.30746282 -1.25683235 -0.94098062 1.65934725 1.02140703 0.00669940
[61] 0.31235021 1.43427683 -0.71091763 0.79646036 0.17397555 0.45575234
[67] 1.13441832 -0.09212644 -0.98045005 1.22923696 -1.03771539 -0.55447263
[73] -1.06134268 -0.57112095 -0.71234073 -0.04908166 -1.23712375 0.10076032
[79] 0.67872001 0.76436949 -1.03376427 -0.04494487 1.38133585 0.53080492
[85] 1.24791892 0.58648918 0.16861563 -0.29153601 1.08787337 -0.85388756
[91] -0.06359805 -0.68930507 0.39487417 0.96115206 -0.61883868 -2.18832142
[97] -1.40949664 0.33430459 -0.56712936 1.15583230
> rowMin(tmp2)
[1] -0.38804718 0.63755340 1.24217871 -0.12764972 2.19192880 0.54020094
[7] -1.08212771 0.65573784 0.29661885 -0.75126420 1.08537909 -0.45443064
[13] -1.41041103 -1.04419373 -0.68941750 -0.32087463 -0.84707038 2.64948936
[19] 0.61037555 -0.21415764 2.16160844 0.58229184 -0.36350820 -0.57647170
[25] -1.29682389 -0.79990742 -0.12720781 1.10917212 -1.16109719 -1.18597162
[31] 2.04677461 -0.76518328 0.62699006 0.22345038 0.50235667 -0.46661063
[37] 0.69403217 -0.16520012 -0.71601839 -0.26158587 1.33119918 -0.47930048
[43] -0.94776481 -2.04683713 -0.32002821 -0.33239046 -1.04976704 1.32398341
[49] -1.47076073 -1.14920297 0.25743844 -0.28062017 -1.23841401 -1.29231020
[55] 0.30746282 -1.25683235 -0.94098062 1.65934725 1.02140703 0.00669940
[61] 0.31235021 1.43427683 -0.71091763 0.79646036 0.17397555 0.45575234
[67] 1.13441832 -0.09212644 -0.98045005 1.22923696 -1.03771539 -0.55447263
[73] -1.06134268 -0.57112095 -0.71234073 -0.04908166 -1.23712375 0.10076032
[79] 0.67872001 0.76436949 -1.03376427 -0.04494487 1.38133585 0.53080492
[85] 1.24791892 0.58648918 0.16861563 -0.29153601 1.08787337 -0.85388756
[91] -0.06359805 -0.68930507 0.39487417 0.96115206 -0.61883868 -2.18832142
[97] -1.40949664 0.33430459 -0.56712936 1.15583230
>
> colMeans(tmp2)
[1] -0.04094756
> colSums(tmp2)
[1] -4.094756
> colVars(tmp2)
[1] 0.962896
> colSd(tmp2)
[1] 0.9812726
> colMax(tmp2)
[1] 2.649489
> colMin(tmp2)
[1] -2.188321
> colMedians(tmp2)
[1] -0.1464249
> colRanges(tmp2)
[,1]
[1,] -2.188321
[2,] 2.649489
>
> 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] 3.6944396 0.4396764 1.9343316 -1.4032246 -4.0332631 0.3266682
[7] 6.9095987 -2.9875141 1.1804545 2.7805546
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.9244390
[2,] 0.2945980
[3,] 0.4413997
[4,] 0.6454268
[5,] 2.3166944
>
> rowApply(tmp,sum)
[1] 4.2604660 -0.5967319 -2.9696625 -1.7039200 7.8533845 -3.1097461
[7] 0.2114282 5.8969780 -0.5502283 -0.4502461
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 6 8 9 8 1 1 7 9 9 10
[2,] 3 6 7 6 8 5 2 8 4 3
[3,] 8 2 8 3 9 9 9 2 7 8
[4,] 2 10 3 1 6 2 4 3 6 9
[5,] 4 5 2 5 7 7 1 7 3 1
[6,] 9 4 1 7 2 8 10 5 5 6
[7,] 10 1 10 9 4 4 6 10 2 7
[8,] 7 3 6 2 5 3 3 1 8 4
[9,] 1 7 4 4 10 6 5 4 10 5
[10,] 5 9 5 10 3 10 8 6 1 2
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -1.6834681 0.6227677 -1.1674208 -3.4850077 3.3598479 1.9435905
[7] 5.4137387 -0.8150924 3.0847240 2.0083572 -0.3368082 -2.8191088
[13] 0.2031243 0.2214400 0.6039256 -0.4230837 1.2904394 4.6301482
[19] -2.5924544 0.6900565
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.9628297
[2,] -0.8911096
[3,] -0.6145614
[4,] 0.2523566
[5,] 0.5326760
>
> rowApply(tmp,sum)
[1] 4.4156281 0.1105616 2.9383190 2.2739802 1.0112272
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 13 5 3 9 4
[2,] 5 4 8 18 18
[3,] 8 10 10 3 8
[4,] 15 3 1 13 1
[5,] 18 6 18 14 16
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.5326760 -0.5199995 0.22700243 0.5825887 1.1493793 0.43932337
[2,] -0.8911096 -1.0682182 -0.11049155 -1.1125749 -0.6984782 1.04352927
[3,] -0.9628297 -0.3118903 0.02149791 -1.3526721 1.3548260 0.63795150
[4,] 0.2523566 1.4129012 -1.28092149 0.5244722 0.5732988 -0.19366443
[5,] -0.6145614 1.1099746 -0.02450807 -2.1268216 0.9808219 0.01645082
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.3034494 0.37255893 1.5736443 0.5369939 0.6751901 -1.8115859
[2,] 1.5447993 -2.70847085 1.1610280 -0.3652391 0.8346370 -0.2140432
[3,] 2.7113943 -0.06434567 1.0911219 0.2896376 -1.2701161 -0.6261035
[4,] 0.4800234 1.29489197 -0.8417095 0.5147980 -0.2759721 0.3053448
[5,] 0.3740723 0.29027319 0.1006393 1.0321668 -0.3005471 -0.4727210
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -1.00735133 0.7248578 -1.12997698 -0.4998465 0.5129567 2.9145242
[2,] 0.01298288 -0.2976016 -0.08288299 -1.2337876 0.4522924 1.8034195
[3,] 1.03573014 -0.4749850 -0.95026218 0.3949791 0.2613731 0.2979492
[4,] -1.42432737 -0.3578011 2.53551749 0.7128115 0.6513636 1.4648966
[5,] 1.58608998 0.6269699 0.23153030 0.2027599 -0.5875463 -1.8506412
[,19] [,20]
[1,] -0.18082478 -0.979932
[2,] -0.04582518 2.086596
[3,] -0.57550588 1.430569
[4,] -1.10859433 -2.965706
[5,] -0.68170425 1.118529
>
>
> 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 -0.4641797 -0.3749045 -2.727155 -1.921556 -0.4914134 -1.645264 0.5378793
col8 col9 col10 col11 col12 col13 col14
row1 0.0004000483 -1.383256 -0.5271481 0.1589976 0.5349682 1.443979 -0.2557581
col15 col16 col17 col18 col19 col20
row1 0.7814928 -0.6016542 1.843868 -1.522915 -1.433663 -1.414495
> tmp[,"col10"]
col10
row1 -0.52714810
row2 0.79183739
row3 0.01667388
row4 -0.54782830
row5 1.61155387
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 -0.4641797 -0.3749045 -2.7271553 -1.921556 -0.4914134 -1.6452641
row5 -0.8881393 0.2319484 0.9854295 -1.265934 -0.4040361 -0.1008964
col7 col8 col9 col10 col11 col12
row1 0.5378793 0.0004000483 -1.3832563 -0.5271481 0.1589976 0.5349682
row5 -0.1342101 1.7919301104 0.2179723 1.6115539 1.5810087 1.0819932
col13 col14 col15 col16 col17 col18 col19
row1 1.4439792 -0.2557581 0.7814928 -0.6016542 1.843868 -1.5229147 -1.433663
row5 -0.1412586 -1.4413355 -0.4978069 0.1000466 -2.462847 0.6356422 -0.480640
col20
row1 -1.41449507
row5 0.03789402
> tmp[,c("col6","col20")]
col6 col20
row1 -1.645264137 -1.41449507
row2 -0.003374685 0.02908367
row3 -0.434985738 -0.13268252
row4 -0.116053265 0.05671610
row5 -0.100896389 0.03789402
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -1.6452641 -1.41449507
row5 -0.1008964 0.03789402
>
>
>
>
> 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 49.289 49.60503 50.75297 50.71513 50.66478 105.1668 50.7259 49.76296
col9 col10 col11 col12 col13 col14 col15 col16
row1 48.87132 48.55814 50.12072 49.80237 49.47834 50.38573 51.03761 50.48809
col17 col18 col19 col20
row1 50.46335 49.53667 51.48053 104.8051
> tmp[,"col10"]
col10
row1 48.55814
row2 29.42298
row3 30.44239
row4 30.22388
row5 50.94356
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.28900 49.60503 50.75297 50.71513 50.66478 105.1668 50.72590 49.76296
row5 51.39481 49.14262 50.83303 48.80966 50.40629 103.0270 49.16848 49.08402
col9 col10 col11 col12 col13 col14 col15 col16
row1 48.87132 48.55814 50.12072 49.80237 49.47834 50.38573 51.03761 50.48809
row5 48.57638 50.94356 51.02075 49.31934 49.44647 51.45227 50.78076 48.48998
col17 col18 col19 col20
row1 50.46335 49.53667 51.48053 104.8051
row5 50.31533 49.20754 49.80526 105.0243
> tmp[,c("col6","col20")]
col6 col20
row1 105.16684 104.80511
row2 73.30295 76.61220
row3 73.95250 76.08512
row4 74.13980 76.78878
row5 103.02704 105.02428
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.1668 104.8051
row5 103.0270 105.0243
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.1668 104.8051
row5 103.0270 105.0243
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -0.9020359
[2,] -0.6034027
[3,] 0.0887717
[4,] -0.1237519
[5,] -0.4527369
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.6588846 1.4224518
[2,] 0.6386416 -2.0648687
[3,] -0.1746332 -2.2134106
[4,] 0.2459622 1.1494402
[5,] -1.1549301 0.2132931
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.48410283 0.24162404
[2,] 1.97454558 0.05730689
[3,] -0.08848195 -0.60653640
[4,] -1.23463173 -1.77664328
[5,] 1.72943893 1.19541167
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.4841028
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.4841028
[2,] 1.9745456
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6]
row3 -0.83973107 -1.328203 -0.6730144 -1.1459664 0.2038635 1.15246708
row1 -0.02571818 2.265384 1.2336268 -0.8792458 -2.0740688 -0.03324405
[,7] [,8] [,9] [,10] [,11] [,12]
row3 -0.8031111 -2.2515655 -0.50290933 0.9821144 1.2114859 1.188639
row1 0.5347843 -0.1611023 0.06530994 1.0262905 0.3788274 -1.415294
[,13] [,14] [,15] [,16] [,17] [,18]
row3 -0.09744651 -1.255194 2.1568249 -1.0286501 0.2953497 0.3963842
row1 -0.48127329 -2.260789 0.5243553 -0.8437029 -0.7475894 -1.7426352
[,19] [,20]
row3 -0.3142375 0.07562971
row1 0.1682933 -0.85228424
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 0.330032 -0.6570939 0.9631918 0.7696798 -1.702161 1.068214 1.897187
[,8] [,9] [,10]
row2 -0.6373193 1.426955 0.4618455
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -0.1456171 -0.3085268 -0.04137557 -1.155914 -0.01884021 1.44579 0.1948713
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 1.414922 1.067378 1.507333 -0.2488716 0.2231354 -0.6133474 -0.85482
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -1.334681 -0.1099442 -0.4263173 -0.0210242 0.7257769 1.218547
>
>
> 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: 0x6000000f0000>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM112b410b12b07"
[2] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM112b45f7fe120"
[3] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM112b444952cdb"
[4] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM112b41db4010a"
[5] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM112b414b046c2"
[6] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM112b440f5752a"
[7] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM112b432df39b7"
[8] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM112b45d463778"
[9] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM112b42ce3d71f"
[10] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM112b422404b3f"
[11] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM112b42b0c26aa"
[12] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM112b42abe78fa"
[13] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM112b43ef87b02"
[14] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM112b42b53e09a"
[15] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM112b4fbeb4af"
>
>
> ### 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: 0x6000000c8420>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x6000000c8420>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x6000000c8420>
> rowMedians(tmp)
[1] -0.533639986 0.148192834 -0.102313191 0.411433250 0.605273526
[6] -0.180596628 0.688471438 0.066900084 -0.254330385 -0.319688196
[11] -0.083967239 -0.944904112 0.061771564 -0.207133893 0.100851536
[16] -0.078162465 -0.150844015 -0.021135376 -0.212919229 0.097632850
[21] 0.029266892 0.173465260 0.432440134 0.128074326 -0.327867380
[26] 0.083777951 -0.083911606 0.201906731 -0.127703812 -0.345563734
[31] -0.341609093 0.056352157 -0.295036768 0.434752170 -0.190510170
[36] -0.287245278 0.014393044 -0.295476342 0.025627554 -0.522302674
[41] 0.070160704 0.195179911 -0.166867280 -0.158359185 -0.232881632
[46] -0.504018657 -0.638659528 -0.058784676 0.267696959 -0.320258740
[51] -0.287175046 0.278825693 -0.230449027 0.330441875 -0.445847448
[56] -0.365683297 -0.095127662 -0.363733915 -0.083056853 -0.238641518
[61] 0.309036897 -0.122531596 0.132687647 -0.401781620 -0.191719161
[66] 0.435215619 0.303984431 -0.066923615 -0.121809463 0.008746772
[71] 0.489490331 0.423668084 -0.326025125 0.018264141 0.041217667
[76] 0.040589008 -0.131477497 0.332942212 0.080108708 -0.294412923
[81] -0.195049582 0.111719600 -0.478595223 0.265535325 0.129265163
[86] -0.343102106 0.743206629 0.088265718 0.027314486 -0.848987773
[91] -0.262591870 0.010619709 0.078965279 -0.146359496 -0.624076614
[96] 0.253598151 0.218903820 0.248865273 -0.671149250 0.228767002
[101] 0.028994340 -0.421217113 0.094365562 0.123278037 -0.145532375
[106] 0.161912619 -0.265001383 0.040216932 -0.017197289 0.384149435
[111] -0.605985474 0.133961970 0.171549494 0.280265496 0.005133942
[116] -0.081123581 0.058578815 0.363916263 -0.325324588 0.258517395
[121] 0.357668586 -0.013807115 -0.106655882 0.005201207 0.077535950
[126] -0.064343830 0.572654111 0.462541441 -0.003128453 -0.068403479
[131] -0.249388698 0.013650684 0.369772368 0.161473877 -0.122638175
[136] -0.640397545 -0.033441546 0.285963818 0.195714703 0.290278259
[141] 0.134254830 -0.317558376 0.260787597 -0.310271998 0.525350123
[146] 0.267478449 -0.650274726 -0.209376665 -0.344759182 -0.583680880
[151] 0.403313201 -0.403624590 -0.087217467 -0.175249313 -0.437228497
[156] -0.104485798 -0.131494510 -0.215177635 0.210579402 0.050884325
[161] -0.482911670 -0.196465478 0.285626506 -0.095791705 -0.260097824
[166] -0.440223598 0.515730785 -0.670168683 -0.537719203 -0.496814784
[171] -0.850793871 -0.209411892 -0.245423118 -0.111186946 0.045323012
[176] -0.130366564 0.061918393 -0.674963732 -0.222430907 0.288800051
[181] -0.343984384 0.391474029 -0.297486304 0.290411198 -0.253285138
[186] -0.308123001 0.467041583 -0.292198920 -0.076023062 -0.376414941
[191] 0.463565432 0.194969239 0.263026540 -0.261632941 -0.784364651
[196] -0.264757623 -0.359986257 0.122144095 -0.037615028 0.661196695
[201] 0.791993516 0.407340762 -0.035553040 -0.622800332 -0.249520332
[206] 0.662789130 0.194612457 -0.535998499 -0.206652980 -0.181952035
[211] 0.208292423 -0.072202876 -0.045400018 -0.139745211 -0.303645314
[216] -0.110436558 0.050048401 -0.246493863 -0.182048181 -0.204517867
[221] 0.497113609 0.113925323 0.216140614 -0.228232556 0.008176261
[226] 0.066298148 -0.199735409 0.018605739 0.142215010 0.049176497
>
> proc.time()
user system elapsed
0.746 3.698 5.083
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: 0x60000246c660>
> .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: 0x60000246c660>
> .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: 0x60000246c660>
> .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: 0x60000246c660>
> 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: 0x600002450060>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002450060>
> .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: 0x600002450060>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002450060>
> .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: 0x600002450060>
> 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: 0x60000245c1e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x60000245c1e0>
> .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: 0x60000245c1e0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x60000245c1e0>
> .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: 0x60000245c1e0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x60000245c1e0>
> .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: 0x60000245c1e0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x60000245c1e0>
> .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: 0x60000245c1e0>
> 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: 0x600002458000>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x600002458000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002458000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002458000>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1174a254853f6" "BufferedMatrixFile1174a2f804e99"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1174a254853f6" "BufferedMatrixFile1174a2f804e99"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002464180>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002464180>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600002464180>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600002464180>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x600002464180>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x600002464180>
> .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: 0x6000024580c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000024580c0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x6000024580c0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x6000024580c0>
> 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: 0x600002450240>
> .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: 0x600002450240>
> rm(P)
>
> proc.time()
user system elapsed
0.123 0.066 0.212
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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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.
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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
0.127 0.039 0.180