Ben Bolstad
| Snapshot Date: 2025-12-18 13:40 -0500 (Thu, 18 Dec 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 2025-12-19 11:35 -0500 (Fri, 19 Dec 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" | 4875 |
| 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: 2025-12-18 18:44:11 -0500 (Thu, 18 Dec 2025) |
| EndedAt: 2025-12-18 18:44:30 -0500 (Thu, 18 Dec 2025) |
| EllapsedTime: 19.3 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
0.130 0.048 0.177
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 Dec 18 18:44:22 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 Dec 18 18:44:22 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: 0x600003f70120>
>
>
>
> 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 Dec 18 18:44:23 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 Dec 18 18:44:23 2025"
>
> ColMode(tmp2)
<pointer: 0x600003f70120>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 100.1105843 1.22251601 0.5428902 0.5558548
[2,] 0.3397642 -0.21886406 -0.6219095 1.0710955
[3,] 0.2892826 0.25511541 1.2727495 0.1294405
[4,] 0.1095607 -0.01029703 -0.6770124 0.8820729
> 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,] 100.1105843 1.22251601 0.5428902 0.5558548
[2,] 0.3397642 0.21886406 0.6219095 1.0710955
[3,] 0.2892826 0.25511541 1.2727495 0.1294405
[4,] 0.1095607 0.01029703 0.6770124 0.8820729
> 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,] 10.0055277 1.1056745 0.7368108 0.7455567
[2,] 0.5828930 0.4678291 0.7886124 1.0349374
[3,] 0.5378500 0.5050895 1.1281620 0.3597784
[4,] 0.3309996 0.1014743 0.8228076 0.9391873
>
> 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,] 225.16586 37.27926 32.91100 33.01142
[2,] 31.16869 29.89716 33.50803 36.42047
[3,] 30.66778 30.30601 37.55437 28.72722
[4,] 28.41956 26.02504 33.90509 35.27395
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x600003f68420>
> exp(tmp5)
<pointer: 0x600003f68420>
> log(tmp5,2)
<pointer: 0x600003f68420>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 468.6532
> Min(tmp5)
[1] 54.16771
> mean(tmp5)
[1] 72.78448
> Sum(tmp5)
[1] 14556.9
> Var(tmp5)
[1] 866.4736
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 89.72015 74.18290 69.08047 71.53620 72.94750 71.20784 71.12458 70.63469
[9] 68.63830 68.77219
> rowSums(tmp5)
[1] 1794.403 1483.658 1381.609 1430.724 1458.950 1424.157 1422.492 1412.694
[9] 1372.766 1375.444
> rowVars(tmp5)
[1] 8024.70847 81.17481 81.36643 79.89368 93.84918 57.17609
[7] 56.68272 62.31572 94.43858 78.06110
> rowSd(tmp5)
[1] 89.580737 9.009706 9.020334 8.938326 9.687579 7.561487 7.528793
[8] 7.894031 9.717951 8.835219
> rowMax(tmp5)
[1] 468.65324 87.22394 86.83940 92.08058 98.21839 83.15569 84.03111
[8] 82.05356 88.90524 88.73322
> rowMin(tmp5)
[1] 56.62567 56.85550 54.43185 54.16771 58.85373 59.75514 58.18138 58.49412
[9] 54.65964 57.88685
>
> colMeans(tmp5)
[1] 110.14799 66.88122 70.28492 68.89706 72.58244 71.88388 72.39050
[8] 71.47685 70.16708 68.18852 73.64554 73.51898 73.23592 74.35438
[15] 68.75166 69.73222 72.52740 69.53359 66.75339 70.73609
> colSums(tmp5)
[1] 1101.4799 668.8122 702.8492 688.9706 725.8244 718.8388 723.9050
[8] 714.7685 701.6708 681.8852 736.4554 735.1898 732.3592 743.5438
[15] 687.5166 697.3222 725.2740 695.3359 667.5339 707.3609
> colVars(tmp5)
[1] 15924.46679 68.01643 46.40418 61.50089 79.94507 111.88207
[7] 157.23744 32.00292 93.53577 29.59901 65.28494 70.76566
[13] 55.44084 56.29545 96.19036 75.17610 105.59114 126.38984
[19] 89.54105 76.02368
> colSd(tmp5)
[1] 126.192182 8.247207 6.812062 7.842251 8.941201 10.577432
[7] 12.539435 5.657113 9.671389 5.440497 8.079910 8.412233
[13] 7.445861 7.503029 9.807669 8.670415 10.275755 11.242323
[19] 9.462613 8.719156
> colMax(tmp5)
[1] 468.65324 79.14532 84.03111 83.86089 83.15569 87.22394 98.21839
[8] 83.57386 92.08058 77.88003 81.00574 84.08319 86.47314 88.90524
[15] 86.98354 81.14393 86.66772 88.73322 78.77950 82.59526
> colMin(tmp5)
[1] 59.15158 54.16771 59.25260 58.48753 58.91813 60.34738 56.14628 62.30982
[9] 58.18138 61.08894 59.41780 58.15337 61.80706 64.88632 58.85373 56.46702
[17] 56.85550 56.62567 54.43185 58.49412
>
>
> ### 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] 89.72015 74.18290 69.08047 71.53620 72.94750 71.20784 71.12458 70.63469
[9] NA 68.77219
> rowSums(tmp5)
[1] 1794.403 1483.658 1381.609 1430.724 1458.950 1424.157 1422.492 1412.694
[9] NA 1375.444
> rowVars(tmp5)
[1] 8024.70847 81.17481 81.36643 79.89368 93.84918 57.17609
[7] 56.68272 62.31572 90.55941 78.06110
> rowSd(tmp5)
[1] 89.580737 9.009706 9.020334 8.938326 9.687579 7.561487 7.528793
[8] 7.894031 9.516271 8.835219
> rowMax(tmp5)
[1] 468.65324 87.22394 86.83940 92.08058 98.21839 83.15569 84.03111
[8] 82.05356 NA 88.73322
> rowMin(tmp5)
[1] 56.62567 56.85550 54.43185 54.16771 58.85373 59.75514 58.18138 58.49412
[9] NA 57.88685
>
> colMeans(tmp5)
[1] 110.14799 66.88122 70.28492 68.89706 72.58244 71.88388 NA
[8] 71.47685 70.16708 68.18852 73.64554 73.51898 73.23592 74.35438
[15] 68.75166 69.73222 72.52740 69.53359 66.75339 70.73609
> colSums(tmp5)
[1] 1101.4799 668.8122 702.8492 688.9706 725.8244 718.8388 NA
[8] 714.7685 701.6708 681.8852 736.4554 735.1898 732.3592 743.5438
[15] 687.5166 697.3222 725.2740 695.3359 667.5339 707.3609
> colVars(tmp5)
[1] 15924.46679 68.01643 46.40418 61.50089 79.94507 111.88207
[7] NA 32.00292 93.53577 29.59901 65.28494 70.76566
[13] 55.44084 56.29545 96.19036 75.17610 105.59114 126.38984
[19] 89.54105 76.02368
> colSd(tmp5)
[1] 126.192182 8.247207 6.812062 7.842251 8.941201 10.577432
[7] NA 5.657113 9.671389 5.440497 8.079910 8.412233
[13] 7.445861 7.503029 9.807669 8.670415 10.275755 11.242323
[19] 9.462613 8.719156
> colMax(tmp5)
[1] 468.65324 79.14532 84.03111 83.86089 83.15569 87.22394 NA
[8] 83.57386 92.08058 77.88003 81.00574 84.08319 86.47314 88.90524
[15] 86.98354 81.14393 86.66772 88.73322 78.77950 82.59526
> colMin(tmp5)
[1] 59.15158 54.16771 59.25260 58.48753 58.91813 60.34738 NA 62.30982
[9] 58.18138 61.08894 59.41780 58.15337 61.80706 64.88632 58.85373 56.46702
[17] 56.85550 56.62567 54.43185 58.49412
>
> Max(tmp5,na.rm=TRUE)
[1] 468.6532
> Min(tmp5,na.rm=TRUE)
[1] 54.16771
> mean(tmp5,na.rm=TRUE)
[1] 72.86809
> Sum(tmp5,na.rm=TRUE)
[1] 14500.75
> Var(tmp5,na.rm=TRUE)
[1] 869.4446
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 89.72015 74.18290 69.08047 71.53620 72.94750 71.20784 71.12458 70.63469
[9] 69.29577 68.77219
> rowSums(tmp5,na.rm=TRUE)
[1] 1794.403 1483.658 1381.609 1430.724 1458.950 1424.157 1422.492 1412.694
[9] 1316.620 1375.444
> rowVars(tmp5,na.rm=TRUE)
[1] 8024.70847 81.17481 81.36643 79.89368 93.84918 57.17609
[7] 56.68272 62.31572 90.55941 78.06110
> rowSd(tmp5,na.rm=TRUE)
[1] 89.580737 9.009706 9.020334 8.938326 9.687579 7.561487 7.528793
[8] 7.894031 9.516271 8.835219
> rowMax(tmp5,na.rm=TRUE)
[1] 468.65324 87.22394 86.83940 92.08058 98.21839 83.15569 84.03111
[8] 82.05356 88.90524 88.73322
> rowMin(tmp5,na.rm=TRUE)
[1] 56.62567 56.85550 54.43185 54.16771 58.85373 59.75514 58.18138 58.49412
[9] 54.65964 57.88685
>
> colMeans(tmp5,na.rm=TRUE)
[1] 110.14799 66.88122 70.28492 68.89706 72.58244 71.88388 74.19542
[8] 71.47685 70.16708 68.18852 73.64554 73.51898 73.23592 74.35438
[15] 68.75166 69.73222 72.52740 69.53359 66.75339 70.73609
> colSums(tmp5,na.rm=TRUE)
[1] 1101.4799 668.8122 702.8492 688.9706 725.8244 718.8388 667.7588
[8] 714.7685 701.6708 681.8852 736.4554 735.1898 732.3592 743.5438
[15] 687.5166 697.3222 725.2740 695.3359 667.5339 707.3609
> colVars(tmp5,na.rm=TRUE)
[1] 15924.46679 68.01643 46.40418 61.50089 79.94507 111.88207
[7] 140.24286 32.00292 93.53577 29.59901 65.28494 70.76566
[13] 55.44084 56.29545 96.19036 75.17610 105.59114 126.38984
[19] 89.54105 76.02368
> colSd(tmp5,na.rm=TRUE)
[1] 126.192182 8.247207 6.812062 7.842251 8.941201 10.577432
[7] 11.842418 5.657113 9.671389 5.440497 8.079910 8.412233
[13] 7.445861 7.503029 9.807669 8.670415 10.275755 11.242323
[19] 9.462613 8.719156
> colMax(tmp5,na.rm=TRUE)
[1] 468.65324 79.14532 84.03111 83.86089 83.15569 87.22394 98.21839
[8] 83.57386 92.08058 77.88003 81.00574 84.08319 86.47314 88.90524
[15] 86.98354 81.14393 86.66772 88.73322 78.77950 82.59526
> colMin(tmp5,na.rm=TRUE)
[1] 59.15158 54.16771 59.25260 58.48753 58.91813 60.34738 59.92837 62.30982
[9] 58.18138 61.08894 59.41780 58.15337 61.80706 64.88632 58.85373 56.46702
[17] 56.85550 56.62567 54.43185 58.49412
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 89.72015 74.18290 69.08047 71.53620 72.94750 71.20784 71.12458 70.63469
[9] NaN 68.77219
> rowSums(tmp5,na.rm=TRUE)
[1] 1794.403 1483.658 1381.609 1430.724 1458.950 1424.157 1422.492 1412.694
[9] 0.000 1375.444
> rowVars(tmp5,na.rm=TRUE)
[1] 8024.70847 81.17481 81.36643 79.89368 93.84918 57.17609
[7] 56.68272 62.31572 NA 78.06110
> rowSd(tmp5,na.rm=TRUE)
[1] 89.580737 9.009706 9.020334 8.938326 9.687579 7.561487 7.528793
[8] 7.894031 NA 8.835219
> rowMax(tmp5,na.rm=TRUE)
[1] 468.65324 87.22394 86.83940 92.08058 98.21839 83.15569 84.03111
[8] 82.05356 NA 88.73322
> rowMin(tmp5,na.rm=TRUE)
[1] 56.62567 56.85550 54.43185 54.16771 58.85373 59.75514 58.18138 58.49412
[9] NA 57.88685
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 114.63788 67.02643 70.18562 70.05368 72.93263 73.16572 NaN
[8] 71.63154 69.60167 68.28719 73.36918 74.09416 73.62014 72.73762
[15] 69.29423 71.20613 70.95625 70.39236 68.09714 69.41840
> colSums(tmp5,na.rm=TRUE)
[1] 1031.7409 603.2379 631.6706 630.4831 656.3937 658.4914 0.0000
[8] 644.6838 626.4150 614.5847 660.3226 666.8475 662.5813 654.6386
[15] 623.6481 640.8552 638.6062 633.5312 612.8743 624.7656
> colVars(tmp5,na.rm=TRUE)
[1] 17688.23513 76.28127 52.09376 54.13873 88.55856 107.38249
[7] NA 35.73409 101.63117 33.18935 72.58635 75.88945
[13] 60.71010 33.92579 104.90234 60.13346 91.01938 133.89192
[19] 80.41995 65.99330
> colSd(tmp5,na.rm=TRUE)
[1] 132.997125 8.733915 7.217601 7.357902 9.410556 10.362552
[7] NA 5.977800 10.081228 5.761020 8.519762 8.711455
[13] 7.791668 5.824585 10.242184 7.754577 9.540408 11.571167
[19] 8.967717 8.123626
> colMax(tmp5,na.rm=TRUE)
[1] 468.65324 79.14532 84.03111 83.86089 83.15569 87.22394 -Inf
[8] 83.57386 92.08058 77.88003 81.00574 84.08319 86.47314 80.57319
[15] 86.98354 81.14393 79.23698 88.73322 78.77950 81.04572
> colMin(tmp5,na.rm=TRUE)
[1] 59.15158 54.16771 59.25260 59.79195 58.91813 61.59549 Inf 62.30982
[9] 58.18138 61.08894 59.41780 58.15337 61.80706 64.88632 58.85373 59.75514
[17] 56.85550 56.62567 54.43185 58.49412
>
>
>
>
> 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] 233.4203 196.4547 190.5375 235.1916 273.0955 285.0970 210.4637 250.5411
[9] 267.9960 181.1985
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 233.4203 196.4547 190.5375 235.1916 273.0955 285.0970 210.4637 250.5411
[9] 267.9960 181.1985
>
>
>
> 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] 2.842171e-14 0.000000e+00 0.000000e+00 -2.842171e-14 -7.105427e-14
[6] 0.000000e+00 1.136868e-13 1.421085e-13 -2.273737e-13 5.684342e-14
[11] 2.842171e-14 -7.105427e-14 -8.526513e-14 1.705303e-13 8.526513e-14
[16] -1.705303e-13 8.526513e-14 0.000000e+00 0.000000e+00 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)
+ }
5 20
6 1
4 7
2 15
10 4
5 5
5 17
5 1
4 4
7 20
4 1
10 3
9 2
6 8
6 6
7 18
1 15
7 14
4 9
6 17
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] 2.489577
> Min(tmp)
[1] -3.016197
> mean(tmp)
[1] 0.1128188
> Sum(tmp)
[1] 11.28188
> Var(tmp)
[1] 1.172176
>
> rowMeans(tmp)
[1] 0.1128188
> rowSums(tmp)
[1] 11.28188
> rowVars(tmp)
[1] 1.172176
> rowSd(tmp)
[1] 1.082671
> rowMax(tmp)
[1] 2.489577
> rowMin(tmp)
[1] -3.016197
>
> colMeans(tmp)
[1] 0.53511306 0.96666555 0.02149241 -0.82074463 -1.98237000 -1.48052491
[7] 0.31341933 0.53788610 0.60616417 -0.81338435 0.69130021 -0.07215014
[13] -0.34830814 -0.02470786 -0.01084059 0.61862249 0.11791596 0.69613472
[19] 2.24001420 -1.86275016 1.28849532 0.24293639 0.12762581 -0.75419083
[25] -1.60494772 1.51008890 1.11410714 0.36164669 -0.22529098 0.40405241
[31] 0.37159013 1.94098848 1.82853809 0.34176767 0.00171682 0.26922438
[37] 0.19950797 -0.67466189 0.90863565 -0.23997478 1.22451248 -0.99933479
[43] 1.18561458 1.09878576 1.64174137 -0.89614709 -0.57763626 -1.58109616
[49] 0.36197751 1.31811357 -0.19827286 -0.87793617 0.67703079 1.01003473
[55] 1.72221042 -0.39740719 0.79751759 -0.38258125 1.46644509 -3.01619710
[61] 0.90851554 0.41131696 -0.89072975 0.89963204 0.52828925 0.43027379
[67] 0.21419150 0.92663373 1.63353427 -1.64954283 -0.36342713 0.08451663
[73] -1.09258101 -1.82457207 -1.16618359 1.53824771 -2.46396211 0.75510987
[79] -0.78892307 0.04947197 0.24792098 -0.61501827 0.56985185 1.53880851
[85] 0.22952284 -0.48491229 0.94358969 1.48345500 0.01639552 -0.98054327
[91] 2.48957673 0.08179014 0.64724719 1.57965470 -0.75478750 -1.10503597
[97] -0.86013741 -0.64238449 -2.24535235 0.08424787
> colSums(tmp)
[1] 0.53511306 0.96666555 0.02149241 -0.82074463 -1.98237000 -1.48052491
[7] 0.31341933 0.53788610 0.60616417 -0.81338435 0.69130021 -0.07215014
[13] -0.34830814 -0.02470786 -0.01084059 0.61862249 0.11791596 0.69613472
[19] 2.24001420 -1.86275016 1.28849532 0.24293639 0.12762581 -0.75419083
[25] -1.60494772 1.51008890 1.11410714 0.36164669 -0.22529098 0.40405241
[31] 0.37159013 1.94098848 1.82853809 0.34176767 0.00171682 0.26922438
[37] 0.19950797 -0.67466189 0.90863565 -0.23997478 1.22451248 -0.99933479
[43] 1.18561458 1.09878576 1.64174137 -0.89614709 -0.57763626 -1.58109616
[49] 0.36197751 1.31811357 -0.19827286 -0.87793617 0.67703079 1.01003473
[55] 1.72221042 -0.39740719 0.79751759 -0.38258125 1.46644509 -3.01619710
[61] 0.90851554 0.41131696 -0.89072975 0.89963204 0.52828925 0.43027379
[67] 0.21419150 0.92663373 1.63353427 -1.64954283 -0.36342713 0.08451663
[73] -1.09258101 -1.82457207 -1.16618359 1.53824771 -2.46396211 0.75510987
[79] -0.78892307 0.04947197 0.24792098 -0.61501827 0.56985185 1.53880851
[85] 0.22952284 -0.48491229 0.94358969 1.48345500 0.01639552 -0.98054327
[91] 2.48957673 0.08179014 0.64724719 1.57965470 -0.75478750 -1.10503597
[97] -0.86013741 -0.64238449 -2.24535235 0.08424787
> 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] 0.53511306 0.96666555 0.02149241 -0.82074463 -1.98237000 -1.48052491
[7] 0.31341933 0.53788610 0.60616417 -0.81338435 0.69130021 -0.07215014
[13] -0.34830814 -0.02470786 -0.01084059 0.61862249 0.11791596 0.69613472
[19] 2.24001420 -1.86275016 1.28849532 0.24293639 0.12762581 -0.75419083
[25] -1.60494772 1.51008890 1.11410714 0.36164669 -0.22529098 0.40405241
[31] 0.37159013 1.94098848 1.82853809 0.34176767 0.00171682 0.26922438
[37] 0.19950797 -0.67466189 0.90863565 -0.23997478 1.22451248 -0.99933479
[43] 1.18561458 1.09878576 1.64174137 -0.89614709 -0.57763626 -1.58109616
[49] 0.36197751 1.31811357 -0.19827286 -0.87793617 0.67703079 1.01003473
[55] 1.72221042 -0.39740719 0.79751759 -0.38258125 1.46644509 -3.01619710
[61] 0.90851554 0.41131696 -0.89072975 0.89963204 0.52828925 0.43027379
[67] 0.21419150 0.92663373 1.63353427 -1.64954283 -0.36342713 0.08451663
[73] -1.09258101 -1.82457207 -1.16618359 1.53824771 -2.46396211 0.75510987
[79] -0.78892307 0.04947197 0.24792098 -0.61501827 0.56985185 1.53880851
[85] 0.22952284 -0.48491229 0.94358969 1.48345500 0.01639552 -0.98054327
[91] 2.48957673 0.08179014 0.64724719 1.57965470 -0.75478750 -1.10503597
[97] -0.86013741 -0.64238449 -2.24535235 0.08424787
> colMin(tmp)
[1] 0.53511306 0.96666555 0.02149241 -0.82074463 -1.98237000 -1.48052491
[7] 0.31341933 0.53788610 0.60616417 -0.81338435 0.69130021 -0.07215014
[13] -0.34830814 -0.02470786 -0.01084059 0.61862249 0.11791596 0.69613472
[19] 2.24001420 -1.86275016 1.28849532 0.24293639 0.12762581 -0.75419083
[25] -1.60494772 1.51008890 1.11410714 0.36164669 -0.22529098 0.40405241
[31] 0.37159013 1.94098848 1.82853809 0.34176767 0.00171682 0.26922438
[37] 0.19950797 -0.67466189 0.90863565 -0.23997478 1.22451248 -0.99933479
[43] 1.18561458 1.09878576 1.64174137 -0.89614709 -0.57763626 -1.58109616
[49] 0.36197751 1.31811357 -0.19827286 -0.87793617 0.67703079 1.01003473
[55] 1.72221042 -0.39740719 0.79751759 -0.38258125 1.46644509 -3.01619710
[61] 0.90851554 0.41131696 -0.89072975 0.89963204 0.52828925 0.43027379
[67] 0.21419150 0.92663373 1.63353427 -1.64954283 -0.36342713 0.08451663
[73] -1.09258101 -1.82457207 -1.16618359 1.53824771 -2.46396211 0.75510987
[79] -0.78892307 0.04947197 0.24792098 -0.61501827 0.56985185 1.53880851
[85] 0.22952284 -0.48491229 0.94358969 1.48345500 0.01639552 -0.98054327
[91] 2.48957673 0.08179014 0.64724719 1.57965470 -0.75478750 -1.10503597
[97] -0.86013741 -0.64238449 -2.24535235 0.08424787
> colMedians(tmp)
[1] 0.53511306 0.96666555 0.02149241 -0.82074463 -1.98237000 -1.48052491
[7] 0.31341933 0.53788610 0.60616417 -0.81338435 0.69130021 -0.07215014
[13] -0.34830814 -0.02470786 -0.01084059 0.61862249 0.11791596 0.69613472
[19] 2.24001420 -1.86275016 1.28849532 0.24293639 0.12762581 -0.75419083
[25] -1.60494772 1.51008890 1.11410714 0.36164669 -0.22529098 0.40405241
[31] 0.37159013 1.94098848 1.82853809 0.34176767 0.00171682 0.26922438
[37] 0.19950797 -0.67466189 0.90863565 -0.23997478 1.22451248 -0.99933479
[43] 1.18561458 1.09878576 1.64174137 -0.89614709 -0.57763626 -1.58109616
[49] 0.36197751 1.31811357 -0.19827286 -0.87793617 0.67703079 1.01003473
[55] 1.72221042 -0.39740719 0.79751759 -0.38258125 1.46644509 -3.01619710
[61] 0.90851554 0.41131696 -0.89072975 0.89963204 0.52828925 0.43027379
[67] 0.21419150 0.92663373 1.63353427 -1.64954283 -0.36342713 0.08451663
[73] -1.09258101 -1.82457207 -1.16618359 1.53824771 -2.46396211 0.75510987
[79] -0.78892307 0.04947197 0.24792098 -0.61501827 0.56985185 1.53880851
[85] 0.22952284 -0.48491229 0.94358969 1.48345500 0.01639552 -0.98054327
[91] 2.48957673 0.08179014 0.64724719 1.57965470 -0.75478750 -1.10503597
[97] -0.86013741 -0.64238449 -2.24535235 0.08424787
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.5351131 0.9666656 0.02149241 -0.8207446 -1.98237 -1.480525 0.3134193
[2,] 0.5351131 0.9666656 0.02149241 -0.8207446 -1.98237 -1.480525 0.3134193
[,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0.5378861 0.6061642 -0.8133844 0.6913002 -0.07215014 -0.3483081
[2,] 0.5378861 0.6061642 -0.8133844 0.6913002 -0.07215014 -0.3483081
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] -0.02470786 -0.01084059 0.6186225 0.117916 0.6961347 2.240014 -1.86275
[2,] -0.02470786 -0.01084059 0.6186225 0.117916 0.6961347 2.240014 -1.86275
[,21] [,22] [,23] [,24] [,25] [,26] [,27]
[1,] 1.288495 0.2429364 0.1276258 -0.7541908 -1.604948 1.510089 1.114107
[2,] 1.288495 0.2429364 0.1276258 -0.7541908 -1.604948 1.510089 1.114107
[,28] [,29] [,30] [,31] [,32] [,33] [,34]
[1,] 0.3616467 -0.225291 0.4040524 0.3715901 1.940988 1.828538 0.3417677
[2,] 0.3616467 -0.225291 0.4040524 0.3715901 1.940988 1.828538 0.3417677
[,35] [,36] [,37] [,38] [,39] [,40] [,41]
[1,] 0.00171682 0.2692244 0.199508 -0.6746619 0.9086357 -0.2399748 1.224512
[2,] 0.00171682 0.2692244 0.199508 -0.6746619 0.9086357 -0.2399748 1.224512
[,42] [,43] [,44] [,45] [,46] [,47] [,48]
[1,] -0.9993348 1.185615 1.098786 1.641741 -0.8961471 -0.5776363 -1.581096
[2,] -0.9993348 1.185615 1.098786 1.641741 -0.8961471 -0.5776363 -1.581096
[,49] [,50] [,51] [,52] [,53] [,54] [,55]
[1,] 0.3619775 1.318114 -0.1982729 -0.8779362 0.6770308 1.010035 1.72221
[2,] 0.3619775 1.318114 -0.1982729 -0.8779362 0.6770308 1.010035 1.72221
[,56] [,57] [,58] [,59] [,60] [,61] [,62]
[1,] -0.3974072 0.7975176 -0.3825813 1.466445 -3.016197 0.9085155 0.411317
[2,] -0.3974072 0.7975176 -0.3825813 1.466445 -3.016197 0.9085155 0.411317
[,63] [,64] [,65] [,66] [,67] [,68] [,69]
[1,] -0.8907298 0.899632 0.5282893 0.4302738 0.2141915 0.9266337 1.633534
[2,] -0.8907298 0.899632 0.5282893 0.4302738 0.2141915 0.9266337 1.633534
[,70] [,71] [,72] [,73] [,74] [,75] [,76]
[1,] -1.649543 -0.3634271 0.08451663 -1.092581 -1.824572 -1.166184 1.538248
[2,] -1.649543 -0.3634271 0.08451663 -1.092581 -1.824572 -1.166184 1.538248
[,77] [,78] [,79] [,80] [,81] [,82] [,83]
[1,] -2.463962 0.7551099 -0.7889231 0.04947197 0.247921 -0.6150183 0.5698518
[2,] -2.463962 0.7551099 -0.7889231 0.04947197 0.247921 -0.6150183 0.5698518
[,84] [,85] [,86] [,87] [,88] [,89] [,90]
[1,] 1.538809 0.2295228 -0.4849123 0.9435897 1.483455 0.01639552 -0.9805433
[2,] 1.538809 0.2295228 -0.4849123 0.9435897 1.483455 0.01639552 -0.9805433
[,91] [,92] [,93] [,94] [,95] [,96] [,97]
[1,] 2.489577 0.08179014 0.6472472 1.579655 -0.7547875 -1.105036 -0.8601374
[2,] 2.489577 0.08179014 0.6472472 1.579655 -0.7547875 -1.105036 -0.8601374
[,98] [,99] [,100]
[1,] -0.6423845 -2.245352 0.08424787
[2,] -0.6423845 -2.245352 0.08424787
>
>
> Max(tmp2)
[1] 3.10921
> Min(tmp2)
[1] -2.215241
> mean(tmp2)
[1] 0.05156729
> Sum(tmp2)
[1] 5.156729
> Var(tmp2)
[1] 0.9201158
>
> rowMeans(tmp2)
[1] 1.351253626 -0.534685122 -1.880674033 1.117526144 0.167970996
[6] -0.114303069 -1.249122474 -0.703419138 0.105388066 0.295822825
[11] 0.649067593 0.565422130 -0.632112156 -0.382201966 -1.259572580
[16] -0.134820276 -0.083053341 -0.672527359 1.285298486 -0.186119058
[21] 0.810896642 0.171778296 -2.215241210 0.007231922 -0.116984757
[26] 0.024961951 -1.973629123 0.512329274 0.104287310 -0.211890164
[31] 0.039324462 -0.335139685 -0.869291929 -0.802619813 -0.188491460
[36] -0.829800339 0.032720373 1.833031505 0.713414457 0.328601482
[41] -1.395939688 -0.193011944 -0.578669929 -1.522817137 1.613440561
[46] -0.825814758 1.047059645 -1.109043460 -0.195724527 0.881330815
[51] -1.777197485 0.437203587 0.388770780 -0.212863434 1.053896916
[56] 0.415872255 -0.193436154 -0.366416846 0.480175778 1.505285920
[61] -0.383868435 0.415724792 -0.012788949 -0.687062516 0.790772753
[66] 0.337811045 -0.060899041 -0.484273340 0.809359294 2.066221831
[71] 0.337725881 -1.035257906 -0.850037383 -0.979371679 1.239364685
[76] -0.326254980 0.792320210 -0.987489739 -0.741060578 0.607973407
[81] 0.056491714 0.580700525 0.384923891 -0.841020600 0.882846244
[86] 0.124726741 0.889162951 0.674426252 -0.050218148 1.864972927
[91] 1.245421994 -1.303345099 -0.670810631 -1.042655617 1.360112298
[96] 0.393038164 0.080957912 2.391066816 -0.014918565 3.109210272
> rowSums(tmp2)
[1] 1.351253626 -0.534685122 -1.880674033 1.117526144 0.167970996
[6] -0.114303069 -1.249122474 -0.703419138 0.105388066 0.295822825
[11] 0.649067593 0.565422130 -0.632112156 -0.382201966 -1.259572580
[16] -0.134820276 -0.083053341 -0.672527359 1.285298486 -0.186119058
[21] 0.810896642 0.171778296 -2.215241210 0.007231922 -0.116984757
[26] 0.024961951 -1.973629123 0.512329274 0.104287310 -0.211890164
[31] 0.039324462 -0.335139685 -0.869291929 -0.802619813 -0.188491460
[36] -0.829800339 0.032720373 1.833031505 0.713414457 0.328601482
[41] -1.395939688 -0.193011944 -0.578669929 -1.522817137 1.613440561
[46] -0.825814758 1.047059645 -1.109043460 -0.195724527 0.881330815
[51] -1.777197485 0.437203587 0.388770780 -0.212863434 1.053896916
[56] 0.415872255 -0.193436154 -0.366416846 0.480175778 1.505285920
[61] -0.383868435 0.415724792 -0.012788949 -0.687062516 0.790772753
[66] 0.337811045 -0.060899041 -0.484273340 0.809359294 2.066221831
[71] 0.337725881 -1.035257906 -0.850037383 -0.979371679 1.239364685
[76] -0.326254980 0.792320210 -0.987489739 -0.741060578 0.607973407
[81] 0.056491714 0.580700525 0.384923891 -0.841020600 0.882846244
[86] 0.124726741 0.889162951 0.674426252 -0.050218148 1.864972927
[91] 1.245421994 -1.303345099 -0.670810631 -1.042655617 1.360112298
[96] 0.393038164 0.080957912 2.391066816 -0.014918565 3.109210272
> 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] 1.351253626 -0.534685122 -1.880674033 1.117526144 0.167970996
[6] -0.114303069 -1.249122474 -0.703419138 0.105388066 0.295822825
[11] 0.649067593 0.565422130 -0.632112156 -0.382201966 -1.259572580
[16] -0.134820276 -0.083053341 -0.672527359 1.285298486 -0.186119058
[21] 0.810896642 0.171778296 -2.215241210 0.007231922 -0.116984757
[26] 0.024961951 -1.973629123 0.512329274 0.104287310 -0.211890164
[31] 0.039324462 -0.335139685 -0.869291929 -0.802619813 -0.188491460
[36] -0.829800339 0.032720373 1.833031505 0.713414457 0.328601482
[41] -1.395939688 -0.193011944 -0.578669929 -1.522817137 1.613440561
[46] -0.825814758 1.047059645 -1.109043460 -0.195724527 0.881330815
[51] -1.777197485 0.437203587 0.388770780 -0.212863434 1.053896916
[56] 0.415872255 -0.193436154 -0.366416846 0.480175778 1.505285920
[61] -0.383868435 0.415724792 -0.012788949 -0.687062516 0.790772753
[66] 0.337811045 -0.060899041 -0.484273340 0.809359294 2.066221831
[71] 0.337725881 -1.035257906 -0.850037383 -0.979371679 1.239364685
[76] -0.326254980 0.792320210 -0.987489739 -0.741060578 0.607973407
[81] 0.056491714 0.580700525 0.384923891 -0.841020600 0.882846244
[86] 0.124726741 0.889162951 0.674426252 -0.050218148 1.864972927
[91] 1.245421994 -1.303345099 -0.670810631 -1.042655617 1.360112298
[96] 0.393038164 0.080957912 2.391066816 -0.014918565 3.109210272
> rowMin(tmp2)
[1] 1.351253626 -0.534685122 -1.880674033 1.117526144 0.167970996
[6] -0.114303069 -1.249122474 -0.703419138 0.105388066 0.295822825
[11] 0.649067593 0.565422130 -0.632112156 -0.382201966 -1.259572580
[16] -0.134820276 -0.083053341 -0.672527359 1.285298486 -0.186119058
[21] 0.810896642 0.171778296 -2.215241210 0.007231922 -0.116984757
[26] 0.024961951 -1.973629123 0.512329274 0.104287310 -0.211890164
[31] 0.039324462 -0.335139685 -0.869291929 -0.802619813 -0.188491460
[36] -0.829800339 0.032720373 1.833031505 0.713414457 0.328601482
[41] -1.395939688 -0.193011944 -0.578669929 -1.522817137 1.613440561
[46] -0.825814758 1.047059645 -1.109043460 -0.195724527 0.881330815
[51] -1.777197485 0.437203587 0.388770780 -0.212863434 1.053896916
[56] 0.415872255 -0.193436154 -0.366416846 0.480175778 1.505285920
[61] -0.383868435 0.415724792 -0.012788949 -0.687062516 0.790772753
[66] 0.337811045 -0.060899041 -0.484273340 0.809359294 2.066221831
[71] 0.337725881 -1.035257906 -0.850037383 -0.979371679 1.239364685
[76] -0.326254980 0.792320210 -0.987489739 -0.741060578 0.607973407
[81] 0.056491714 0.580700525 0.384923891 -0.841020600 0.882846244
[86] 0.124726741 0.889162951 0.674426252 -0.050218148 1.864972927
[91] 1.245421994 -1.303345099 -0.670810631 -1.042655617 1.360112298
[96] 0.393038164 0.080957912 2.391066816 -0.014918565 3.109210272
>
> colMeans(tmp2)
[1] 0.05156729
> colSums(tmp2)
[1] 5.156729
> colVars(tmp2)
[1] 0.9201158
> colSd(tmp2)
[1] 0.9592267
> colMax(tmp2)
[1] 3.10921
> colMin(tmp2)
[1] -2.215241
> colMedians(tmp2)
[1] 0.01609694
> colRanges(tmp2)
[,1]
[1,] -2.215241
[2,] 3.109210
>
> 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] 2.5500210 2.9564451 3.9306304 -3.0094744 -2.4211252 2.0644033
[7] 3.8951788 -0.7586551 -2.3800392 1.7205459
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.5306238
[2,] -0.3052192
[3,] 0.0259193
[4,] 0.4448385
[5,] 2.1708287
>
> rowApply(tmp,sum)
[1] 3.94683865 0.02838444 -3.35741294 1.15340499 2.26617317 6.35558301
[7] -1.66798454 -2.17622571 1.17406406 0.82510552
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 6 3 8 5 9 8 6 2 3 4
[2,] 4 8 1 9 6 4 10 4 9 8
[3,] 8 6 7 7 8 2 9 6 8 7
[4,] 3 4 5 3 2 3 4 9 2 6
[5,] 10 1 9 6 4 1 3 10 6 1
[6,] 9 5 3 8 3 9 1 7 7 5
[7,] 5 9 2 2 10 10 7 1 5 10
[8,] 2 2 4 4 7 7 5 8 1 9
[9,] 1 10 10 1 1 5 8 3 4 3
[10,] 7 7 6 10 5 6 2 5 10 2
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 4.7006877 1.6966054 5.2326090 2.8393490 3.3054484 0.6904145
[7] 4.2041492 -3.9931124 -0.9749422 -3.3389143 -2.4521782 0.1852862
[13] -2.8673857 -1.4119925 2.4292806 -2.1968368 -2.2385641 0.4789891
[19] -0.2338996 -3.3820063
> colApply(tmp,quantile)[,1]
[,1]
[1,] 0.4988112
[2,] 0.9459065
[3,] 0.9579490
[4,] 1.1407914
[5,] 1.1572295
>
> rowApply(tmp,sum)
[1] -2.9735665 10.8309469 -2.1510795 -0.4187777 -2.6145363
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 14 13 18 16 19
[2,] 17 5 9 7 20
[3,] 20 14 20 17 4
[4,] 9 4 19 20 15
[5,] 16 20 10 14 9
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.4988112 1.3302698 1.9193069 -0.4046260 1.00573183 -0.1970131
[2,] 1.1407914 -0.1298562 1.1660746 -0.5581900 2.08620080 1.2326437
[3,] 1.1572295 -0.3759143 2.0320564 1.2654502 -0.37485920 -0.7266863
[4,] 0.9459065 -0.2147264 1.1146613 2.2497365 0.65169550 0.7001280
[5,] 0.9579490 1.0868326 -0.9994903 0.2869783 -0.06332051 -0.3186578
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.7527251 -2.2257811 -1.26987659 -0.2012939 -2.74206283 -0.41260745
[2,] 1.8727610 1.2929182 1.79639282 -0.8849815 0.68524853 -0.09529467
[3,] 0.6419293 -0.1803768 -1.37933859 -0.4432774 0.27637789 -0.91706913
[4,] 0.3910046 -1.2590422 -0.21362260 -0.5979871 -0.08693185 1.56576127
[5,] 0.5457291 -1.6208305 0.09150278 -1.2113745 -0.58480992 0.04449617
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.8633194 1.6988402 0.1422895 -0.5530424 -1.612019 -0.04222438
[2,] -1.1848904 0.2011093 1.7057948 0.6626209 0.387376 -0.11623650
[3,] -0.6079747 0.8984910 -0.7579595 -0.7734821 0.529613 0.12459305
[4,] 0.1838354 -2.1917807 1.4457544 -1.6386828 -1.740169 -0.02168069
[5,] -0.3950366 -2.0186523 -0.1065985 0.1057495 0.196635 0.53453758
[,19] [,20]
[1,] 1.4542983 -1.25197274
[2,] -1.3997961 0.97026023
[3,] 0.7463147 -3.28619658
[4,] -1.8766492 0.17401095
[5,] 0.8419327 0.01189185
>
>
> 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 -0.4173099 0.05668397 0.2642244 -0.3061434 1.808356 -1.501111 -0.9160042
col8 col9 col10 col11 col12 col13 col14
row1 -1.037022 -0.05456617 -0.9657978 0.1041867 1.061933 0.9765431 0.4154449
col15 col16 col17 col18 col19 col20
row1 -1.123795 -0.6445995 -0.2987451 0.7760271 -0.7780108 0.01278314
> tmp[,"col10"]
col10
row1 -0.9657978
row2 -0.6084917
row3 0.9639715
row4 -0.3388435
row5 1.8590475
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 -0.4173099 0.05668397 0.2642244 -0.3061434 1.8083563 -1.5011115
row5 -0.3550221 -0.34962967 1.7884629 0.1347426 0.8372178 0.8259134
col7 col8 col9 col10 col11 col12
row1 -0.9160042 -1.037022 -0.05456617 -0.9657978 0.104186750 1.0619335
row5 -0.7673258 1.453008 0.34917035 1.8590475 -0.001889258 -0.3923041
col13 col14 col15 col16 col17 col18 col19
row1 0.9765431 0.4154449 -1.1237949 -0.6445995 -0.2987451 0.7760271 -0.7780108
row5 1.6962198 -0.9324305 -0.0727687 1.0504536 -0.5204179 1.0057402 1.0125407
col20
row1 0.01278314
row5 0.85667004
> tmp[,c("col6","col20")]
col6 col20
row1 -1.5011115 0.01278314
row2 0.2207528 -0.55294949
row3 -0.4934750 -1.14732716
row4 1.8458146 0.59653592
row5 0.8259134 0.85667004
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -1.5011115 0.01278314
row5 0.8259134 0.85667004
>
>
>
>
> 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 49.40462 51.9042 50.40014 48.3039 51.8588 104.5135 51.53294 50.48649
col9 col10 col11 col12 col13 col14 col15 col16
row1 51.51886 49.35114 51.49336 49.88486 48.81597 48.40617 48.95559 48.49416
col17 col18 col19 col20
row1 50.30808 49.63163 49.33416 107.3307
> tmp[,"col10"]
col10
row1 49.35114
row2 30.35335
row3 30.61719
row4 29.46352
row5 51.38116
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.40462 51.90420 50.40014 48.30390 51.85880 104.5135 51.53294 50.48649
row5 51.60204 50.34536 49.43422 50.54746 49.46522 106.2009 50.62624 50.74930
col9 col10 col11 col12 col13 col14 col15 col16
row1 51.51886 49.35114 51.49336 49.88486 48.81597 48.40617 48.95559 48.49416
row5 50.18920 51.38116 50.24352 50.82100 50.84814 50.43989 50.33477 49.22933
col17 col18 col19 col20
row1 50.30808 49.63163 49.33416 107.3307
row5 51.05635 49.11794 49.75287 104.5869
> tmp[,c("col6","col20")]
col6 col20
row1 104.51347 107.33071
row2 74.97510 75.43972
row3 76.32324 75.88832
row4 74.49043 75.82244
row5 106.20092 104.58693
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.5135 107.3307
row5 106.2009 104.5869
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.5135 107.3307
row5 106.2009 104.5869
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.8465544
[2,] 0.1402164
[3,] -0.9840253
[4,] 0.5316208
[5,] -0.8005553
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.1270684 1.1143696
[2,] 2.4904311 0.5626898
[3,] -1.5348908 0.8380398
[4,] -0.1937163 -0.1113629
[5,] 0.8432523 0.5162441
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 1.5711017 -0.34236839
[2,] -0.7781087 -1.24485332
[3,] -0.6401341 0.04792711
[4,] -1.1816652 -0.71267550
[5,] 0.1251590 2.06687731
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 1.571102
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 1.5711017
[2,] -0.7781087
>
>
>
> 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 0.6482191 -0.04078097 -0.2086375 0.6539213 1.6698262 0.5255976
row1 -2.0137983 -1.53771385 2.1559068 -0.3499747 -0.9428763 -1.0840517
[,7] [,8] [,9] [,10] [,11] [,12]
row3 0.26159648 -0.8210932 -0.68924508 0.2326546 0.7768813 -1.4799388
row1 0.08667052 -0.4953783 -0.09715016 -0.3750137 -1.6616586 0.5049398
[,13] [,14] [,15] [,16] [,17] [,18] [,19]
row3 0.34449361 0.5416133 0.3743657 0.8002712 -0.5797033 -0.4466915 1.1480797
row1 0.09498935 0.2284273 0.6187607 -0.6345476 0.6178020 -1.2291219 0.4709502
[,20]
row3 -1.1063396
row1 -0.9970773
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 0.42704 0.2423721 1.204015 1.019524 0.8146094 -0.1288879 0.9484981
[,8] [,9] [,10]
row2 1.423025 1.295783 -0.855985
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.9075953 0.4897486 -0.7273524 -1.523476 1.683942 -0.8690809 1.561935
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.7601895 -0.6111125 -0.450207 0.1290095 -0.3260723 -1.127266 -0.06564033
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.1825663 0.8281985 -1.602177 -0.1077271 0.2255938 -0.5426779
>
>
> 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: 0x600003f40000>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM32cf37c54b8e"
[2] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM32cf79e3743c"
[3] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM32cf43e44da8"
[4] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM32cf41a6736a"
[5] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM32cf16e355d2"
[6] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM32cf271759bb"
[7] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM32cf6e041809"
[8] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM32cf4ec62f4c"
[9] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM32cf354b4efb"
[10] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM32cf632e5c12"
[11] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM32cf789ed49c"
[12] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM32cf3988ba2"
[13] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM32cf13f73a86"
[14] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM32cf4c233da7"
[15] "/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests/BM32cf1da4c5fe"
>
>
> ### 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: 0x600003f4c060>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x600003f4c060>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.23-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x600003f4c060>
> rowMedians(tmp)
[1] -0.072734209 0.286621894 0.041182723 0.122109091 0.556912683
[6] -0.221482180 -0.598601356 0.457987771 -0.470859213 -0.210249446
[11] -0.087096167 -0.421078698 0.472536372 -0.194542212 0.203999083
[16] 0.044751750 -0.859924230 -0.532906131 0.010754317 0.425589722
[21] -0.287311235 -0.270795585 0.064710930 -0.014620116 -0.090718575
[26] 0.235997084 -0.352809318 -0.120025670 0.552091876 -0.427663906
[31] -0.294458356 0.533874352 -0.184040563 0.147893505 0.473243690
[36] -0.563371047 0.589130340 0.263672215 -0.428645575 -0.167249047
[41] -0.216415417 0.307414945 0.121374671 -0.156472063 0.372511249
[46] -0.002244571 0.071579801 0.187934779 -0.513320373 -0.271998376
[51] 0.253190846 0.045701066 0.121370471 0.139897567 -0.343801747
[56] 0.145219217 -0.406126509 -0.562715422 -0.107210998 0.434372144
[61] -0.379811856 0.128517091 0.034771316 0.086101750 -0.112045303
[66] 0.322330547 0.132596182 0.557057593 0.155037756 -0.377852269
[71] 0.022632908 0.177940143 -0.106090478 0.049243583 -0.213723165
[76] -0.831807345 0.001697831 -0.016380294 -0.202260078 -0.004366357
[81] -0.039024774 -0.040923554 0.257053934 -0.429650717 -0.178230094
[86] -0.140023044 -0.245677491 -0.164846632 -0.189822832 -0.493221223
[91] 0.014310102 0.196951150 0.127253482 0.115898335 0.033720629
[96] -0.184927294 0.412050753 -0.151375343 -0.093563429 -0.171711967
[101] 0.045630994 0.122737956 -0.210667624 0.241754538 0.196344864
[106] -0.248503093 -0.317396768 0.349083402 0.055395366 0.401918062
[111] 0.130560957 0.557220252 -0.045970294 0.161441409 -0.040254754
[116] -0.008726054 -0.500057511 -0.175607818 -0.270262643 0.636898511
[121] -0.251733751 0.559146791 0.276557072 0.313376158 -0.610386487
[126] 0.702106274 -0.403211519 -0.339747344 0.146004588 0.463636388
[131] 0.078734400 -0.108722648 -0.359707705 0.112252346 0.409030305
[136] -0.492800968 -0.053931107 -0.554081412 0.109460588 -0.323177245
[141] 0.414573606 0.024204096 -0.111093424 -0.214410902 0.203581780
[146] 0.093395383 -0.539153199 -0.156879317 -0.144330259 0.405741689
[151] -0.232482229 -0.094625131 0.146668537 -0.136367638 -0.171210003
[156] 0.257392899 0.023503383 0.213730159 -0.277507756 0.691524210
[161] -0.461334537 0.225109643 0.534044571 0.326675131 -0.027305332
[166] 0.411635744 -0.044179418 0.220244740 0.294079166 -0.108368762
[171] -0.280418057 0.237478554 0.328321788 0.264132185 0.533048515
[176] -0.068656523 0.188054638 -0.435488461 0.170026709 0.178435928
[181] 0.425002014 0.132647171 -0.322399662 0.517231010 -0.145491263
[186] 0.148539355 -0.098293363 -0.569789990 -0.156529878 0.253920322
[191] -0.122462163 0.379204053 0.455692738 -0.195080159 -0.048889288
[196] -0.935903378 0.475245852 -0.228333312 -0.231579358 -0.219282886
[201] -0.192280500 0.068849373 -0.418086827 -0.035633353 -0.394219729
[206] 0.097315348 -0.032890512 0.016654238 0.182067438 0.180856737
[211] 0.234220532 0.087805416 -0.305024414 -0.323127870 0.665573977
[216] -0.251033362 0.034645612 -0.438625827 -0.623425377 -0.290519010
[221] -0.207130213 -0.115014244 0.443673820 0.068810608 -0.291379346
[226] 0.043521031 -0.214748591 0.731785859 -0.178668231 -0.184040022
>
> proc.time()
user system elapsed
0.690 3.535 4.692
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: 0x600003e4c000>
> .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: 0x600003e4c000>
> .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: 0x600003e4c000>
> .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: 0x600003e4c000>
> 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: 0x600003e40360>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003e40360>
> .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: 0x600003e40360>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003e40360>
> .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: 0x600003e40360>
> 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: 0x600003e40540>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003e40540>
> .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: 0x600003e40540>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600003e40540>
> .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: 0x600003e40540>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x600003e40540>
> .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: 0x600003e40540>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x600003e40540>
> .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: 0x600003e40540>
> 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: 0x600003e40720>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x600003e40720>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003e40720>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003e40720>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile36fa73647d5" "BufferedMatrixFile36fa7ca5f4a5"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile36fa73647d5" "BufferedMatrixFile36fa7ca5f4a5"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003e6c6c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003e6c6c0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600003e6c6c0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600003e6c6c0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x600003e6c6c0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x600003e6c6c0>
> .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: 0x600003e6c840>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003e6c840>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600003e6c840>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x600003e6c840>
> 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: 0x600003e6ca20>
> .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: 0x600003e6ca20>
> rm(P)
>
> proc.time()
user system elapsed
0.136 0.060 0.197
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R Under development (unstable) (2025-11-04 r88984) -- "Unsuffered Consequences"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20
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You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
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Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
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> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.133 0.035 0.163