Ben Bolstad
| Snapshot Date: 2025-10-10 13:45 -0400 (Fri, 10 Oct 2025) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: devel |
| git_last_commit: 0147962 |
| git_last_commit_date: 2025-04-15 09:39:39 -0400 (Tue, 15 Apr 2025) |
| Back to Multiple platform build/check report for BioC 3.22: simplified long |
|
This page was generated on 2025-10-11 12:05 -0400 (Sat, 11 Oct 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 24.04.3 LTS) | x86_64 | 4.5.1 Patched (2025-08-23 r88802) -- "Great Square Root" | 4864 |
| lconway | macOS 12.7.1 Monterey | x86_64 | 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root" | 4652 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root" | 4597 |
| taishan | Linux (openEuler 24.03 LTS) | aarch64 | 4.5.0 (2025-04-11) -- "How About a Twenty-Six" | 4586 |
| 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 255/2346 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.73.0 (landing page) Ben Bolstad
| nebbiolo2 | Linux (Ubuntu 24.04.3 LTS) / x86_64 | OK | OK | OK | | ||||||||
| lconway | macOS 12.7.1 Monterey / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| kjohnson3 | macOS 13.7.7 Ventura / arm64 | OK | OK | WARNINGS | OK | | ||||||||
| taishan | Linux (openEuler 24.03 LTS) / aarch64 | OK | OK | 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: 1.73.0 |
| 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_1.73.0.tar.gz |
| StartedAt: 2025-10-10 18:31:11 -0400 (Fri, 10 Oct 2025) |
| EndedAt: 2025-10-10 18:31:26 -0400 (Fri, 10 Oct 2025) |
| EllapsedTime: 15.2 seconds |
| RetCode: 0 |
| Status: WARNINGS |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 1 |
##############################################################################
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###
### Running command:
###
### /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings BufferedMatrix_1.73.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.5.1 Patched (2025-09-10 r88807)
* 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 13.7.7
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.73.0’
* 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-3.22-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 ... NOTE
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, 2 NOTEs
See
‘/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/Library/Frameworks/R.framework/Versions/4.5-arm64/Resources/library’
* installing *source* package ‘BufferedMatrix’ ...
** this is package ‘BufferedMatrix’ version ‘1.73.0’
** 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/4.5-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 version 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root"
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
0.109 0.034 0.138
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root"
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-3.22-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 480828 25.7 1056624 56.5 NA 634340 33.9
Vcells 891019 6.8 8388608 64.0 196608 2109889 16.1
>
>
>
>
> ##
> ## 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] "Fri Oct 10 18:31:19 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] "Fri Oct 10 18:31:19 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: 0x600002cfc300>
>
>
>
> 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] "Fri Oct 10 18:31:20 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] "Fri Oct 10 18:31:21 2025"
>
> ColMode(tmp2)
<pointer: 0x600002cfc300>
>
>
>
> ### 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,] 101.1344930 0.5971114 1.35395672 -1.0297240
[2,] -0.7378142 1.4939873 1.92199531 -0.1673301
[3,] -0.9037645 -0.8828565 0.09366975 1.2298642
[4,] -0.8132233 -0.1789470 -0.32541662 0.4003331
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.22-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,] 101.1344930 0.5971114 1.35395672 1.0297240
[2,] 0.7378142 1.4939873 1.92199531 0.1673301
[3,] 0.9037645 0.8828565 0.09366975 1.2298642
[4,] 0.8132233 0.1789470 0.32541662 0.4003331
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.22-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,] 10.0565647 0.7727298 1.1635965 1.0147532
[2,] 0.8589611 1.2222877 1.3863605 0.4090600
[3,] 0.9506653 0.9396044 0.3060551 1.1089924
[4,] 0.9017890 0.4230213 0.5704530 0.6327188
>
> 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-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 226.70014 33.32441 37.98992 36.17726
[2,] 34.32743 38.71686 40.78560 29.25793
[3,] 35.41042 35.27890 28.15422 37.31979
[4,] 34.83111 29.40916 31.02995 31.72752
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x600002cf0000>
> exp(tmp5)
<pointer: 0x600002cf0000>
> log(tmp5,2)
<pointer: 0x600002cf0000>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 471.8466
> Min(tmp5)
[1] 53.248
> mean(tmp5)
[1] 72.38709
> Sum(tmp5)
[1] 14477.42
> Var(tmp5)
[1] 880.4165
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 91.40397 69.42225 73.63594 68.85082 65.49072 69.63469 75.09326 68.92200
[9] 69.28861 72.12867
> rowSums(tmp5)
[1] 1828.079 1388.445 1472.719 1377.016 1309.814 1392.694 1501.865 1378.440
[9] 1385.772 1442.573
> rowVars(tmp5)
[1] 8084.27606 55.52201 87.82387 66.08278 55.84592 76.05049
[7] 104.60740 51.14474 70.22421 76.33227
> rowSd(tmp5)
[1] 89.912602 7.451309 9.371439 8.129132 7.473013 8.720693 10.227776
[8] 7.151555 8.379989 8.736834
> rowMax(tmp5)
[1] 471.84664 84.88988 88.68716 82.96216 86.26825 87.43302 100.07357
[8] 88.39324 89.34310 85.85974
> rowMin(tmp5)
[1] 57.46699 57.62903 54.67253 53.77019 53.69582 53.24800 59.30582 60.16246
[9] 54.28612 58.40234
>
> colMeans(tmp5)
[1] 111.12426 68.61135 69.72106 69.50426 71.17839 67.83884 66.17523
[8] 74.54389 66.79037 68.64753 72.21117 71.49380 71.13674 69.81793
[15] 70.45810 76.82831 71.68560 72.90102 70.58847 66.48552
> colSums(tmp5)
[1] 1111.2426 686.1135 697.2106 695.0426 711.7839 678.3884 661.7523
[8] 745.4389 667.9037 686.4753 722.1117 714.9380 711.3674 698.1793
[15] 704.5810 768.2831 716.8560 729.0102 705.8847 664.8552
> colVars(tmp5)
[1] 16078.86552 50.97790 67.31782 104.36542 36.96424 42.93882
[7] 61.18597 78.57441 84.19586 109.26999 66.85267 170.70767
[13] 77.77921 91.09518 56.12563 33.81852 90.31087 60.78784
[19] 101.97901 100.43615
> colSd(tmp5)
[1] 126.802467 7.139881 8.204744 10.215939 6.079823 6.552772
[7] 7.822146 8.864221 9.175830 10.453229 8.176348 13.065514
[13] 8.819252 9.544380 7.491704 5.815370 9.503203 7.796656
[19] 10.098466 10.021784
> colMax(tmp5)
[1] 471.84664 80.58408 84.88988 87.43302 79.59927 79.36854 82.96216
[8] 85.61178 87.09319 92.15606 89.34310 100.07357 86.53520 85.85974
[15] 79.01206 86.26825 88.39324 85.67549 84.80677 88.19750
> colMin(tmp5)
[1] 62.52148 61.21131 58.59932 58.09480 61.94813 59.97846 57.62903 61.41930
[9] 55.95024 54.67253 58.83894 57.70079 57.43271 53.77019 58.76736 68.67909
[17] 53.69582 58.73141 54.28612 53.24800
>
>
> ### 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] 91.40397 69.42225 73.63594 68.85082 65.49072 69.63469 75.09326 68.92200
[9] 69.28861 NA
> rowSums(tmp5)
[1] 1828.079 1388.445 1472.719 1377.016 1309.814 1392.694 1501.865 1378.440
[9] 1385.772 NA
> rowVars(tmp5)
[1] 8084.27606 55.52201 87.82387 66.08278 55.84592 76.05049
[7] 104.60740 51.14474 70.22421 73.15700
> rowSd(tmp5)
[1] 89.912602 7.451309 9.371439 8.129132 7.473013 8.720693 10.227776
[8] 7.151555 8.379989 8.553186
> rowMax(tmp5)
[1] 471.84664 84.88988 88.68716 82.96216 86.26825 87.43302 100.07357
[8] 88.39324 89.34310 NA
> rowMin(tmp5)
[1] 57.46699 57.62903 54.67253 53.77019 53.69582 53.24800 59.30582 60.16246
[9] 54.28612 NA
>
> colMeans(tmp5)
[1] 111.12426 68.61135 69.72106 69.50426 71.17839 67.83884 66.17523
[8] NA 66.79037 68.64753 72.21117 71.49380 71.13674 69.81793
[15] 70.45810 76.82831 71.68560 72.90102 70.58847 66.48552
> colSums(tmp5)
[1] 1111.2426 686.1135 697.2106 695.0426 711.7839 678.3884 661.7523
[8] NA 667.9037 686.4753 722.1117 714.9380 711.3674 698.1793
[15] 704.5810 768.2831 716.8560 729.0102 705.8847 664.8552
> colVars(tmp5)
[1] 16078.86552 50.97790 67.31782 104.36542 36.96424 42.93882
[7] 61.18597 NA 84.19586 109.26999 66.85267 170.70767
[13] 77.77921 91.09518 56.12563 33.81852 90.31087 60.78784
[19] 101.97901 100.43615
> colSd(tmp5)
[1] 126.802467 7.139881 8.204744 10.215939 6.079823 6.552772
[7] 7.822146 NA 9.175830 10.453229 8.176348 13.065514
[13] 8.819252 9.544380 7.491704 5.815370 9.503203 7.796656
[19] 10.098466 10.021784
> colMax(tmp5)
[1] 471.84664 80.58408 84.88988 87.43302 79.59927 79.36854 82.96216
[8] NA 87.09319 92.15606 89.34310 100.07357 86.53520 85.85974
[15] 79.01206 86.26825 88.39324 85.67549 84.80677 88.19750
> colMin(tmp5)
[1] 62.52148 61.21131 58.59932 58.09480 61.94813 59.97846 57.62903 NA
[9] 55.95024 54.67253 58.83894 57.70079 57.43271 53.77019 58.76736 68.67909
[17] 53.69582 58.73141 54.28612 53.24800
>
> Max(tmp5,na.rm=TRUE)
[1] 471.8466
> Min(tmp5,na.rm=TRUE)
[1] 53.248
> mean(tmp5,na.rm=TRUE)
[1] 72.3318
> Sum(tmp5,na.rm=TRUE)
[1] 14394.03
> Var(tmp5,na.rm=TRUE)
[1] 884.2486
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.40397 69.42225 73.63594 68.85082 65.49072 69.63469 75.09326 68.92200
[9] 69.28861 71.53598
> rowSums(tmp5,na.rm=TRUE)
[1] 1828.079 1388.445 1472.719 1377.016 1309.814 1392.694 1501.865 1378.440
[9] 1385.772 1359.184
> rowVars(tmp5,na.rm=TRUE)
[1] 8084.27606 55.52201 87.82387 66.08278 55.84592 76.05049
[7] 104.60740 51.14474 70.22421 73.15700
> rowSd(tmp5,na.rm=TRUE)
[1] 89.912602 7.451309 9.371439 8.129132 7.473013 8.720693 10.227776
[8] 7.151555 8.379989 8.553186
> rowMax(tmp5,na.rm=TRUE)
[1] 471.84664 84.88988 88.68716 82.96216 86.26825 87.43302 100.07357
[8] 88.39324 89.34310 85.85974
> rowMin(tmp5,na.rm=TRUE)
[1] 57.46699 57.62903 54.67253 53.77019 53.69582 53.24800 59.30582 60.16246
[9] 54.28612 58.40234
>
> colMeans(tmp5,na.rm=TRUE)
[1] 111.12426 68.61135 69.72106 69.50426 71.17839 67.83884 66.17523
[8] 73.56102 66.79037 68.64753 72.21117 71.49380 71.13674 69.81793
[15] 70.45810 76.82831 71.68560 72.90102 70.58847 66.48552
> colSums(tmp5,na.rm=TRUE)
[1] 1111.2426 686.1135 697.2106 695.0426 711.7839 678.3884 661.7523
[8] 662.0492 667.9037 686.4753 722.1117 714.9380 711.3674 698.1793
[15] 704.5810 768.2831 716.8560 729.0102 705.8847 664.8552
> colVars(tmp5,na.rm=TRUE)
[1] 16078.86552 50.97790 67.31782 104.36542 36.96424 42.93882
[7] 61.18597 77.52816 84.19586 109.26999 66.85267 170.70767
[13] 77.77921 91.09518 56.12563 33.81852 90.31087 60.78784
[19] 101.97901 100.43615
> colSd(tmp5,na.rm=TRUE)
[1] 126.802467 7.139881 8.204744 10.215939 6.079823 6.552772
[7] 7.822146 8.805007 9.175830 10.453229 8.176348 13.065514
[13] 8.819252 9.544380 7.491704 5.815370 9.503203 7.796656
[19] 10.098466 10.021784
> colMax(tmp5,na.rm=TRUE)
[1] 471.84664 80.58408 84.88988 87.43302 79.59927 79.36854 82.96216
[8] 85.61178 87.09319 92.15606 89.34310 100.07357 86.53520 85.85974
[15] 79.01206 86.26825 88.39324 85.67549 84.80677 88.19750
> colMin(tmp5,na.rm=TRUE)
[1] 62.52148 61.21131 58.59932 58.09480 61.94813 59.97846 57.62903 61.41930
[9] 55.95024 54.67253 58.83894 57.70079 57.43271 53.77019 58.76736 68.67909
[17] 53.69582 58.73141 54.28612 53.24800
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.40397 69.42225 73.63594 68.85082 65.49072 69.63469 75.09326 68.92200
[9] 69.28861 NaN
> rowSums(tmp5,na.rm=TRUE)
[1] 1828.079 1388.445 1472.719 1377.016 1309.814 1392.694 1501.865 1378.440
[9] 1385.772 0.000
> rowVars(tmp5,na.rm=TRUE)
[1] 8084.27606 55.52201 87.82387 66.08278 55.84592 76.05049
[7] 104.60740 51.14474 70.22421 NA
> rowSd(tmp5,na.rm=TRUE)
[1] 89.912602 7.451309 9.371439 8.129132 7.473013 8.720693 10.227776
[8] 7.151555 8.379989 NA
> rowMax(tmp5,na.rm=TRUE)
[1] 471.84664 84.88988 88.68716 82.96216 86.26825 87.43302 100.07357
[8] 88.39324 89.34310 NA
> rowMin(tmp5,na.rm=TRUE)
[1] 57.46699 57.62903 54.67253 53.77019 53.69582 53.24800 59.30582 60.16246
[9] 54.28612 NA
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 115.37123 67.75648 69.64812 70.66629 70.28890 68.07576 66.86040
[8] NaN 67.72237 68.86190 71.81552 72.25798 70.64388 68.03551
[15] 69.54801 77.52845 72.61369 71.48163 69.36663 66.21233
> colSums(tmp5,na.rm=TRUE)
[1] 1038.3411 609.8084 626.8331 635.9966 632.6001 612.6818 601.7436
[8] 0.0000 609.5014 619.7571 646.3397 650.3219 635.7949 612.3196
[15] 625.9321 697.7560 653.5232 643.3347 624.2997 595.9110
> colVars(tmp5,na.rm=TRUE)
[1] 17885.81044 49.12861 75.67269 102.22024 32.68386 47.67473
[7] 63.55279 NA 84.94825 122.41174 73.44819 185.47637
[13] 84.76889 66.74047 53.82339 32.53116 91.90936 45.72145
[19] 97.93135 112.15106
> colSd(tmp5,na.rm=TRUE)
[1] 133.737842 7.009180 8.699005 10.110402 5.716980 6.904689
[7] 7.972000 NA 9.216738 11.063984 8.570192 13.618971
[13] 9.207002 8.169484 7.336443 5.703609 9.586937 6.761764
[19] 9.896027 10.590140
> colMax(tmp5,na.rm=TRUE)
[1] 471.84664 80.58408 84.88988 87.43302 79.59927 79.36854 82.96216
[8] -Inf 87.09319 92.15606 89.34310 100.07357 86.53520 82.02010
[15] 79.01206 86.26825 88.39324 82.86690 84.80677 88.19750
> colMin(tmp5,na.rm=TRUE)
[1] 62.52148 61.21131 58.59932 58.09480 61.94813 59.97846 57.62903 Inf
[9] 55.95024 54.67253 58.83894 57.70079 57.43271 53.77019 58.76736 68.67909
[17] 53.69582 58.73141 54.28612 53.24800
>
>
>
>
> 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] 282.52031 272.17883 230.48255 157.23240 219.93147 323.92001 254.33751
[8] 318.03452 198.58777 93.31591
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 282.52031 272.17883 230.48255 157.23240 219.93147 323.92001 254.33751
[8] 318.03452 198.58777 93.31591
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col <- 3
> cat(which.row," ",which.col,"\n")
1 3
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
[1] 5.684342e-14 -1.421085e-14 1.136868e-13 3.410605e-13 1.136868e-13
[6] 5.684342e-14 -8.526513e-14 1.136868e-13 -2.273737e-13 4.263256e-14
[11] -1.421085e-14 -1.989520e-13 -2.842171e-14 -1.136868e-13 9.947598e-14
[16] -1.421085e-14 0.000000e+00 8.526513e-14 -4.263256e-14 0.000000e+00
>
>
>
>
>
>
>
>
>
>
> ## 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)
+ }
1 16
7 11
3 8
5 8
9 6
2 6
3 9
3 8
9 12
6 19
10 10
7 12
4 20
3 17
6 13
4 6
10 20
8 16
7 13
7 2
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] 2.520193
> Min(tmp)
[1] -2.340398
> mean(tmp)
[1] 0.2376022
> Sum(tmp)
[1] 23.76022
> Var(tmp)
[1] 1.048314
>
> rowMeans(tmp)
[1] 0.2376022
> rowSums(tmp)
[1] 23.76022
> rowVars(tmp)
[1] 1.048314
> rowSd(tmp)
[1] 1.023872
> rowMax(tmp)
[1] 2.520193
> rowMin(tmp)
[1] -2.340398
>
> colMeans(tmp)
[1] 0.114534611 0.768335131 0.142161749 -1.685330624 -0.814083733
[6] -1.073772947 0.520182693 1.902616091 -1.110830384 0.791292422
[11] -0.866683599 0.915320664 -0.393765206 0.749031410 2.106709502
[16] -0.774867497 1.330785178 -0.547723669 -2.155004837 0.899831659
[21] -0.195151007 1.338870991 -1.222902182 -0.660275553 0.035585495
[26] 0.744594136 -0.353641649 -1.097437039 1.506568730 0.531350161
[31] -2.048899060 1.795454283 -0.312576507 -0.046647666 -0.527369541
[36] 0.597891363 0.624754456 1.571749156 0.945943688 1.490948812
[41] 0.166329792 -0.675274580 -0.004722173 0.556984937 1.235546241
[46] 1.154783427 0.159510541 0.294594180 0.602659830 1.683318310
[51] 1.403299661 0.232336722 -0.465377863 -0.969430629 -0.463031728
[56] 0.825098276 0.912407484 0.825322298 -0.014311117 0.012552885
[61] 2.383397331 -0.617267528 -2.340397673 1.094656541 -0.245613606
[66] 0.125821513 0.503403188 -0.428632670 0.492349417 1.437623211
[71] -2.182718507 -0.667420125 -0.235642699 0.646326399 0.096009697
[76] 1.171919206 2.520192637 -0.926631811 0.989677235 -0.597851953
[81] 0.853024583 -0.071231571 0.735002254 1.694102463 1.075596418
[86] 0.944634366 1.123785097 -0.568325459 -1.450989622 0.116873899
[91] -0.432817690 -1.110991435 0.977689645 1.728168981 -0.336203056
[96] 0.178759131 0.207772910 -0.040728073 0.635620655 1.271125994
> colSums(tmp)
[1] 0.114534611 0.768335131 0.142161749 -1.685330624 -0.814083733
[6] -1.073772947 0.520182693 1.902616091 -1.110830384 0.791292422
[11] -0.866683599 0.915320664 -0.393765206 0.749031410 2.106709502
[16] -0.774867497 1.330785178 -0.547723669 -2.155004837 0.899831659
[21] -0.195151007 1.338870991 -1.222902182 -0.660275553 0.035585495
[26] 0.744594136 -0.353641649 -1.097437039 1.506568730 0.531350161
[31] -2.048899060 1.795454283 -0.312576507 -0.046647666 -0.527369541
[36] 0.597891363 0.624754456 1.571749156 0.945943688 1.490948812
[41] 0.166329792 -0.675274580 -0.004722173 0.556984937 1.235546241
[46] 1.154783427 0.159510541 0.294594180 0.602659830 1.683318310
[51] 1.403299661 0.232336722 -0.465377863 -0.969430629 -0.463031728
[56] 0.825098276 0.912407484 0.825322298 -0.014311117 0.012552885
[61] 2.383397331 -0.617267528 -2.340397673 1.094656541 -0.245613606
[66] 0.125821513 0.503403188 -0.428632670 0.492349417 1.437623211
[71] -2.182718507 -0.667420125 -0.235642699 0.646326399 0.096009697
[76] 1.171919206 2.520192637 -0.926631811 0.989677235 -0.597851953
[81] 0.853024583 -0.071231571 0.735002254 1.694102463 1.075596418
[86] 0.944634366 1.123785097 -0.568325459 -1.450989622 0.116873899
[91] -0.432817690 -1.110991435 0.977689645 1.728168981 -0.336203056
[96] 0.178759131 0.207772910 -0.040728073 0.635620655 1.271125994
> 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] 0.114534611 0.768335131 0.142161749 -1.685330624 -0.814083733
[6] -1.073772947 0.520182693 1.902616091 -1.110830384 0.791292422
[11] -0.866683599 0.915320664 -0.393765206 0.749031410 2.106709502
[16] -0.774867497 1.330785178 -0.547723669 -2.155004837 0.899831659
[21] -0.195151007 1.338870991 -1.222902182 -0.660275553 0.035585495
[26] 0.744594136 -0.353641649 -1.097437039 1.506568730 0.531350161
[31] -2.048899060 1.795454283 -0.312576507 -0.046647666 -0.527369541
[36] 0.597891363 0.624754456 1.571749156 0.945943688 1.490948812
[41] 0.166329792 -0.675274580 -0.004722173 0.556984937 1.235546241
[46] 1.154783427 0.159510541 0.294594180 0.602659830 1.683318310
[51] 1.403299661 0.232336722 -0.465377863 -0.969430629 -0.463031728
[56] 0.825098276 0.912407484 0.825322298 -0.014311117 0.012552885
[61] 2.383397331 -0.617267528 -2.340397673 1.094656541 -0.245613606
[66] 0.125821513 0.503403188 -0.428632670 0.492349417 1.437623211
[71] -2.182718507 -0.667420125 -0.235642699 0.646326399 0.096009697
[76] 1.171919206 2.520192637 -0.926631811 0.989677235 -0.597851953
[81] 0.853024583 -0.071231571 0.735002254 1.694102463 1.075596418
[86] 0.944634366 1.123785097 -0.568325459 -1.450989622 0.116873899
[91] -0.432817690 -1.110991435 0.977689645 1.728168981 -0.336203056
[96] 0.178759131 0.207772910 -0.040728073 0.635620655 1.271125994
> colMin(tmp)
[1] 0.114534611 0.768335131 0.142161749 -1.685330624 -0.814083733
[6] -1.073772947 0.520182693 1.902616091 -1.110830384 0.791292422
[11] -0.866683599 0.915320664 -0.393765206 0.749031410 2.106709502
[16] -0.774867497 1.330785178 -0.547723669 -2.155004837 0.899831659
[21] -0.195151007 1.338870991 -1.222902182 -0.660275553 0.035585495
[26] 0.744594136 -0.353641649 -1.097437039 1.506568730 0.531350161
[31] -2.048899060 1.795454283 -0.312576507 -0.046647666 -0.527369541
[36] 0.597891363 0.624754456 1.571749156 0.945943688 1.490948812
[41] 0.166329792 -0.675274580 -0.004722173 0.556984937 1.235546241
[46] 1.154783427 0.159510541 0.294594180 0.602659830 1.683318310
[51] 1.403299661 0.232336722 -0.465377863 -0.969430629 -0.463031728
[56] 0.825098276 0.912407484 0.825322298 -0.014311117 0.012552885
[61] 2.383397331 -0.617267528 -2.340397673 1.094656541 -0.245613606
[66] 0.125821513 0.503403188 -0.428632670 0.492349417 1.437623211
[71] -2.182718507 -0.667420125 -0.235642699 0.646326399 0.096009697
[76] 1.171919206 2.520192637 -0.926631811 0.989677235 -0.597851953
[81] 0.853024583 -0.071231571 0.735002254 1.694102463 1.075596418
[86] 0.944634366 1.123785097 -0.568325459 -1.450989622 0.116873899
[91] -0.432817690 -1.110991435 0.977689645 1.728168981 -0.336203056
[96] 0.178759131 0.207772910 -0.040728073 0.635620655 1.271125994
> colMedians(tmp)
[1] 0.114534611 0.768335131 0.142161749 -1.685330624 -0.814083733
[6] -1.073772947 0.520182693 1.902616091 -1.110830384 0.791292422
[11] -0.866683599 0.915320664 -0.393765206 0.749031410 2.106709502
[16] -0.774867497 1.330785178 -0.547723669 -2.155004837 0.899831659
[21] -0.195151007 1.338870991 -1.222902182 -0.660275553 0.035585495
[26] 0.744594136 -0.353641649 -1.097437039 1.506568730 0.531350161
[31] -2.048899060 1.795454283 -0.312576507 -0.046647666 -0.527369541
[36] 0.597891363 0.624754456 1.571749156 0.945943688 1.490948812
[41] 0.166329792 -0.675274580 -0.004722173 0.556984937 1.235546241
[46] 1.154783427 0.159510541 0.294594180 0.602659830 1.683318310
[51] 1.403299661 0.232336722 -0.465377863 -0.969430629 -0.463031728
[56] 0.825098276 0.912407484 0.825322298 -0.014311117 0.012552885
[61] 2.383397331 -0.617267528 -2.340397673 1.094656541 -0.245613606
[66] 0.125821513 0.503403188 -0.428632670 0.492349417 1.437623211
[71] -2.182718507 -0.667420125 -0.235642699 0.646326399 0.096009697
[76] 1.171919206 2.520192637 -0.926631811 0.989677235 -0.597851953
[81] 0.853024583 -0.071231571 0.735002254 1.694102463 1.075596418
[86] 0.944634366 1.123785097 -0.568325459 -1.450989622 0.116873899
[91] -0.432817690 -1.110991435 0.977689645 1.728168981 -0.336203056
[96] 0.178759131 0.207772910 -0.040728073 0.635620655 1.271125994
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.1145346 0.7683351 0.1421617 -1.685331 -0.8140837 -1.073773 0.5201827
[2,] 0.1145346 0.7683351 0.1421617 -1.685331 -0.8140837 -1.073773 0.5201827
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 1.902616 -1.11083 0.7912924 -0.8666836 0.9153207 -0.3937652 0.7490314
[2,] 1.902616 -1.11083 0.7912924 -0.8666836 0.9153207 -0.3937652 0.7490314
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 2.10671 -0.7748675 1.330785 -0.5477237 -2.155005 0.8998317 -0.195151
[2,] 2.10671 -0.7748675 1.330785 -0.5477237 -2.155005 0.8998317 -0.195151
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 1.338871 -1.222902 -0.6602756 0.03558549 0.7445941 -0.3536416 -1.097437
[2,] 1.338871 -1.222902 -0.6602756 0.03558549 0.7445941 -0.3536416 -1.097437
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 1.506569 0.5313502 -2.048899 1.795454 -0.3125765 -0.04664767 -0.5273695
[2,] 1.506569 0.5313502 -2.048899 1.795454 -0.3125765 -0.04664767 -0.5273695
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 0.5978914 0.6247545 1.571749 0.9459437 1.490949 0.1663298 -0.6752746
[2,] 0.5978914 0.6247545 1.571749 0.9459437 1.490949 0.1663298 -0.6752746
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.004722173 0.5569849 1.235546 1.154783 0.1595105 0.2945942 0.6026598
[2,] -0.004722173 0.5569849 1.235546 1.154783 0.1595105 0.2945942 0.6026598
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 1.683318 1.4033 0.2323367 -0.4653779 -0.9694306 -0.4630317 0.8250983
[2,] 1.683318 1.4033 0.2323367 -0.4653779 -0.9694306 -0.4630317 0.8250983
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 0.9124075 0.8253223 -0.01431112 0.01255288 2.383397 -0.6172675 -2.340398
[2,] 0.9124075 0.8253223 -0.01431112 0.01255288 2.383397 -0.6172675 -2.340398
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 1.094657 -0.2456136 0.1258215 0.5034032 -0.4286327 0.4923494 1.437623
[2,] 1.094657 -0.2456136 0.1258215 0.5034032 -0.4286327 0.4923494 1.437623
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -2.182719 -0.6674201 -0.2356427 0.6463264 0.0960097 1.171919 2.520193
[2,] -2.182719 -0.6674201 -0.2356427 0.6463264 0.0960097 1.171919 2.520193
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -0.9266318 0.9896772 -0.597852 0.8530246 -0.07123157 0.7350023 1.694102
[2,] -0.9266318 0.9896772 -0.597852 0.8530246 -0.07123157 0.7350023 1.694102
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 1.075596 0.9446344 1.123785 -0.5683255 -1.45099 0.1168739 -0.4328177
[2,] 1.075596 0.9446344 1.123785 -0.5683255 -1.45099 0.1168739 -0.4328177
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -1.110991 0.9776896 1.728169 -0.3362031 0.1787591 0.2077729 -0.04072807
[2,] -1.110991 0.9776896 1.728169 -0.3362031 0.1787591 0.2077729 -0.04072807
[,99] [,100]
[1,] 0.6356207 1.271126
[2,] 0.6356207 1.271126
>
>
> Max(tmp2)
[1] 2.693734
> Min(tmp2)
[1] -2.718435
> mean(tmp2)
[1] 0.06331641
> Sum(tmp2)
[1] 6.331641
> Var(tmp2)
[1] 1.185648
>
> rowMeans(tmp2)
[1] -0.492468297 0.668242350 2.376120044 0.577765832 -0.910094190
[6] -0.127862715 -0.358877251 0.298268152 -0.461604602 -1.305622230
[11] -0.014850333 0.705981693 -0.768389670 0.710728895 0.493014456
[16] -2.718434573 -0.493203850 -0.944352552 -0.827043238 1.424127918
[21] 0.488482300 0.961920499 -0.005916629 0.977712185 0.947798423
[26] -0.553417002 -1.103861681 1.126211961 1.495314002 1.215333038
[31] 1.827762982 0.226520778 -1.924212118 -0.893918736 0.129676132
[36] -0.105513843 0.594967207 -0.373440789 -0.775320314 1.063311190
[41] -0.875860153 -1.794235153 -0.081316160 0.298332718 -0.508310599
[46] 1.166650874 1.028778112 -0.561838117 1.182014179 0.318512004
[51] 1.284973939 1.356948074 -1.613835403 -0.022479502 0.798237333
[56] -0.312801770 -1.973802467 0.530721594 1.120625416 0.801044717
[61] -1.032546002 -0.264008454 0.903626904 -0.507965885 2.054876347
[66] 2.619557111 0.553266687 0.426604797 0.273080019 -2.219073496
[71] 1.188780414 -1.618624114 0.256991574 -1.555829531 -0.644008609
[76] -0.849480560 0.112550305 -0.091683065 -0.297097332 0.007324808
[81] 0.398753372 -0.359845608 -1.708053133 2.563204615 0.351203901
[86] 0.895449814 0.422090142 -0.438068038 -0.167394415 1.213315553
[91] -1.311871207 -0.085959350 -0.145031365 -0.530199432 -1.091216429
[96] 2.693734262 0.499669277 -0.834057171 0.934186814 -1.577827372
> rowSums(tmp2)
[1] -0.492468297 0.668242350 2.376120044 0.577765832 -0.910094190
[6] -0.127862715 -0.358877251 0.298268152 -0.461604602 -1.305622230
[11] -0.014850333 0.705981693 -0.768389670 0.710728895 0.493014456
[16] -2.718434573 -0.493203850 -0.944352552 -0.827043238 1.424127918
[21] 0.488482300 0.961920499 -0.005916629 0.977712185 0.947798423
[26] -0.553417002 -1.103861681 1.126211961 1.495314002 1.215333038
[31] 1.827762982 0.226520778 -1.924212118 -0.893918736 0.129676132
[36] -0.105513843 0.594967207 -0.373440789 -0.775320314 1.063311190
[41] -0.875860153 -1.794235153 -0.081316160 0.298332718 -0.508310599
[46] 1.166650874 1.028778112 -0.561838117 1.182014179 0.318512004
[51] 1.284973939 1.356948074 -1.613835403 -0.022479502 0.798237333
[56] -0.312801770 -1.973802467 0.530721594 1.120625416 0.801044717
[61] -1.032546002 -0.264008454 0.903626904 -0.507965885 2.054876347
[66] 2.619557111 0.553266687 0.426604797 0.273080019 -2.219073496
[71] 1.188780414 -1.618624114 0.256991574 -1.555829531 -0.644008609
[76] -0.849480560 0.112550305 -0.091683065 -0.297097332 0.007324808
[81] 0.398753372 -0.359845608 -1.708053133 2.563204615 0.351203901
[86] 0.895449814 0.422090142 -0.438068038 -0.167394415 1.213315553
[91] -1.311871207 -0.085959350 -0.145031365 -0.530199432 -1.091216429
[96] 2.693734262 0.499669277 -0.834057171 0.934186814 -1.577827372
> 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] -0.492468297 0.668242350 2.376120044 0.577765832 -0.910094190
[6] -0.127862715 -0.358877251 0.298268152 -0.461604602 -1.305622230
[11] -0.014850333 0.705981693 -0.768389670 0.710728895 0.493014456
[16] -2.718434573 -0.493203850 -0.944352552 -0.827043238 1.424127918
[21] 0.488482300 0.961920499 -0.005916629 0.977712185 0.947798423
[26] -0.553417002 -1.103861681 1.126211961 1.495314002 1.215333038
[31] 1.827762982 0.226520778 -1.924212118 -0.893918736 0.129676132
[36] -0.105513843 0.594967207 -0.373440789 -0.775320314 1.063311190
[41] -0.875860153 -1.794235153 -0.081316160 0.298332718 -0.508310599
[46] 1.166650874 1.028778112 -0.561838117 1.182014179 0.318512004
[51] 1.284973939 1.356948074 -1.613835403 -0.022479502 0.798237333
[56] -0.312801770 -1.973802467 0.530721594 1.120625416 0.801044717
[61] -1.032546002 -0.264008454 0.903626904 -0.507965885 2.054876347
[66] 2.619557111 0.553266687 0.426604797 0.273080019 -2.219073496
[71] 1.188780414 -1.618624114 0.256991574 -1.555829531 -0.644008609
[76] -0.849480560 0.112550305 -0.091683065 -0.297097332 0.007324808
[81] 0.398753372 -0.359845608 -1.708053133 2.563204615 0.351203901
[86] 0.895449814 0.422090142 -0.438068038 -0.167394415 1.213315553
[91] -1.311871207 -0.085959350 -0.145031365 -0.530199432 -1.091216429
[96] 2.693734262 0.499669277 -0.834057171 0.934186814 -1.577827372
> rowMin(tmp2)
[1] -0.492468297 0.668242350 2.376120044 0.577765832 -0.910094190
[6] -0.127862715 -0.358877251 0.298268152 -0.461604602 -1.305622230
[11] -0.014850333 0.705981693 -0.768389670 0.710728895 0.493014456
[16] -2.718434573 -0.493203850 -0.944352552 -0.827043238 1.424127918
[21] 0.488482300 0.961920499 -0.005916629 0.977712185 0.947798423
[26] -0.553417002 -1.103861681 1.126211961 1.495314002 1.215333038
[31] 1.827762982 0.226520778 -1.924212118 -0.893918736 0.129676132
[36] -0.105513843 0.594967207 -0.373440789 -0.775320314 1.063311190
[41] -0.875860153 -1.794235153 -0.081316160 0.298332718 -0.508310599
[46] 1.166650874 1.028778112 -0.561838117 1.182014179 0.318512004
[51] 1.284973939 1.356948074 -1.613835403 -0.022479502 0.798237333
[56] -0.312801770 -1.973802467 0.530721594 1.120625416 0.801044717
[61] -1.032546002 -0.264008454 0.903626904 -0.507965885 2.054876347
[66] 2.619557111 0.553266687 0.426604797 0.273080019 -2.219073496
[71] 1.188780414 -1.618624114 0.256991574 -1.555829531 -0.644008609
[76] -0.849480560 0.112550305 -0.091683065 -0.297097332 0.007324808
[81] 0.398753372 -0.359845608 -1.708053133 2.563204615 0.351203901
[86] 0.895449814 0.422090142 -0.438068038 -0.167394415 1.213315553
[91] -1.311871207 -0.085959350 -0.145031365 -0.530199432 -1.091216429
[96] 2.693734262 0.499669277 -0.834057171 0.934186814 -1.577827372
>
> colMeans(tmp2)
[1] 0.06331641
> colSums(tmp2)
[1] 6.331641
> colVars(tmp2)
[1] 1.185648
> colSd(tmp2)
[1] 1.088874
> colMax(tmp2)
[1] 2.693734
> colMin(tmp2)
[1] -2.718435
> colMedians(tmp2)
[1] 0.0007040892
> colRanges(tmp2)
[,1]
[1,] -2.718435
[2,] 2.693734
>
> dataset1 <- matrix(dataset1,1,100)
>
> agree.checks(tmp,dataset1)
>
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>
>
> tmp <- createBufferedMatrix(10,10)
>
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
[1] 4.2611685 0.9000831 0.9404204 -1.3918639 0.2780806 2.5841477
[7] 3.8109852 -5.8737308 -1.1874174 -1.4616377
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.8422230
[2,] 0.2140414
[3,] 0.5481248
[4,] 0.6554770
[5,] 1.1808213
>
> rowApply(tmp,sum)
[1] 4.8266644 1.0501542 2.5913363 -1.8417180 -4.2026093 -1.7515120
[7] 0.9888708 0.3745492 1.7242480 -0.8997477
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 7 7 8 5 9 7 3 6 9 9
[2,] 10 1 6 6 8 10 4 1 5 7
[3,] 1 10 4 10 7 1 7 8 2 4
[4,] 6 4 5 7 5 4 6 10 1 5
[5,] 5 2 2 4 2 6 9 9 8 2
[6,] 9 3 10 1 10 8 5 7 3 6
[7,] 2 8 9 9 4 2 8 4 10 10
[8,] 4 6 3 3 3 5 1 2 4 8
[9,] 3 9 7 2 6 9 2 3 6 3
[10,] 8 5 1 8 1 3 10 5 7 1
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 0.5459795 0.6349372 -3.6579404 -0.8441014 -5.0193416 -0.9795203
[7] 3.1728468 0.9525276 0.3056716 0.3854650 -0.7951322 -1.5512578
[13] -3.6890283 -1.6816764 4.1409483 -2.8295649 2.1815781 -3.5067736
[19] 0.2547858 -1.1493885
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.9503659
[2,] -0.2045128
[3,] 0.2091895
[4,] 0.7457448
[5,] 0.7459239
>
> rowApply(tmp,sum)
[1] -1.835322 -2.132845 -4.360969 1.745081 -6.544930
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 4 15 11 17 19
[2,] 17 8 19 13 4
[3,] 8 3 9 3 7
[4,] 14 11 7 14 3
[5,] 1 18 15 2 1
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -0.9503659 0.8948305 -0.2812252 0.46198334 -3.2115260 0.4864357
[2,] 0.2091895 -0.6241609 -1.1538560 0.06264147 1.1890989 -0.7093291
[3,] -0.2045128 1.2087340 -0.3479322 -0.43502651 0.2781605 -0.1474239
[4,] 0.7459239 0.3755465 -1.1276376 0.45176208 -1.4335424 -0.8362660
[5,] 0.7457448 -1.2200129 -0.7472893 -1.38546179 -1.8415326 0.2270631
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.1944063 1.62231676 0.3144230 1.34514299 -0.1750943 -0.46968665
[2,] -1.5223012 -0.48080472 0.1924942 0.07008223 0.7783557 -0.63385364
[3,] 1.9624529 -0.22166947 -1.8219173 0.07484603 -0.3646513 -0.07963241
[4,] 2.0158682 0.10058584 1.4555527 0.54485377 -0.8641669 0.31649311
[5,] 0.5224207 -0.06790076 0.1651191 -1.64946005 -0.1695754 -0.68457822
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.94540526 0.17860590 0.8624131 -1.16678381 0.001831014 -1.4586605
[2,] -1.32584729 -0.75167262 1.2145431 0.13768746 0.612516350 -0.7174474
[3,] -1.66678887 0.59641756 0.9896072 -0.93192407 1.011383984 -1.8161694
[4,] 0.06980983 -1.79270037 -0.1716948 -0.05384654 0.733305782 1.2135677
[5,] 0.17920330 0.08767314 1.2460797 -0.81469796 -0.177459049 -0.7280640
[,19] [,20]
[1,] 1.2833644 -0.8223276
[2,] 1.5944118 -0.2745931
[3,] -1.5794298 -0.8654933
[4,] -0.1977442 0.1994109
[5,] -0.8458163 0.6136146
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.22-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-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 655 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.22-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-3.22-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 1.49642 -0.6278628 -1.207437 -0.02605397 0.7526464 -1.429819 0.0729492
col8 col9 col10 col11 col12 col13 col14
row1 -1.459768 0.03571971 1.041663 0.7315044 -0.1902335 1.5075 -1.796161
col15 col16 col17 col18 col19 col20
row1 -0.794977 -0.4121361 -0.4092943 0.3735239 0.02255935 0.1678212
> tmp[,"col10"]
col10
row1 1.0416633
row2 1.5251871
row3 2.1657320
row4 -0.2610055
row5 0.9300610
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 1.496420 -0.6278628 -1.20743697 -0.02605397 0.7526464 -1.429819
row5 -2.816275 0.4592583 -0.06965204 0.66057885 -1.2298171 0.446489
col7 col8 col9 col10 col11 col12
row1 0.0729492 -1.4597684 0.03571971 1.041663 0.73150442 -0.1902335
row5 -0.8302109 0.7254292 -0.96477113 0.930061 -0.09878689 -1.6751808
col13 col14 col15 col16 col17 col18
row1 1.5075003 -1.7961609 -0.794977 -0.41213609 -0.40929434 0.3735239
row5 -0.3007963 -0.1315662 0.579779 0.06158639 -0.09307035 0.6787542
col19 col20
row1 0.02255935 0.1678212
row5 -0.57096246 -0.7173856
> tmp[,c("col6","col20")]
col6 col20
row1 -1.4298189 0.1678212
row2 -1.4064819 -0.2417847
row3 -0.2080847 -1.2973385
row4 2.0001210 0.2940056
row5 0.4464890 -0.7173856
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -1.429819 0.1678212
row5 0.446489 -0.7173856
>
>
>
>
> 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 49.21315 50.02978 50.56985 48.99229 50.80627 105.4079 50.14402 50.53583
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.10384 51.15541 47.96356 49.30781 49.65687 51.41775 49.58154 49.6671
col17 col18 col19 col20
row1 49.55662 51.06227 48.12124 105.9291
> tmp[,"col10"]
col10
row1 51.15541
row2 29.64185
row3 29.12134
row4 30.50645
row5 49.47186
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.21315 50.02978 50.56985 48.99229 50.80627 105.4079 50.14402 50.53583
row5 50.57988 50.37491 48.91269 48.40758 49.05818 105.9970 51.09906 51.31303
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.10384 51.15541 47.96356 49.30781 49.65687 51.41775 49.58154 49.66710
row5 51.69323 49.47186 49.65225 49.18145 50.00342 49.97654 50.86839 52.00881
col17 col18 col19 col20
row1 49.55662 51.06227 48.12124 105.9291
row5 50.10866 50.50873 49.74908 104.6006
> tmp[,c("col6","col20")]
col6 col20
row1 105.40794 105.92910
row2 72.24226 76.79238
row3 76.15866 75.67902
row4 74.36788 76.06171
row5 105.99700 104.60060
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.4079 105.9291
row5 105.9970 104.6006
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.4079 105.9291
row5 105.9970 104.6006
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.8517563
[2,] -0.1617516
[3,] -1.1139433
[4,] -0.8132366
[5,] -1.2731828
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.3534620 -0.6481357
[2,] 0.7163648 2.3154803
[3,] 1.8234039 -0.5530963
[4,] -0.6141751 -0.6646904
[5,] -1.1816891 -0.1492571
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.8927807 -1.74479342
[2,] -1.6846524 0.54821753
[3,] 0.5024614 0.69231108
[4,] -1.5614437 0.01864581
[5,] 0.9164098 0.15721058
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.8927807
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.8927807
[2,] -1.6846524
>
>
>
> 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 0.3173606 -0.2229325 1.0133217 -0.05302029 0.8734208 0.3196395
row1 0.7830911 0.6111892 -0.4530588 -0.28304359 1.1925192 0.3619477
[,7] [,8] [,9] [,10] [,11] [,12]
row3 -0.04334423 1.851480 -0.4197083 1.0261668 -0.03417576 0.1800297
row1 1.61163851 -1.929345 -2.4535095 -0.2955091 0.57591497 0.5919238
[,13] [,14] [,15] [,16] [,17] [,18] [,19]
row3 -1.608878 -0.3258429 -0.1213267 0.1912843 -2.924415 -0.3210069 1.310946
row1 1.355490 -2.1030787 -0.3996619 0.2174695 1.827045 -0.9386575 1.468075
[,20]
row3 -0.742535
row1 -2.237862
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 1.963609 0.2740768 0.5885796 -1.317353 1.604115 -1.285689 -2.040565
[,8] [,9] [,10]
row2 -0.3787843 0.2682513 0.5642938
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -1.59916 -0.2664227 0.3045543 -1.634612 -0.4221616 0.002739641 1.925371
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.7203763 -0.7422528 1.797233 -1.560534 -0.1737344 -0.6245893 -1.164986
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.3702932 1.85724 1.318663 0.8842911 0.8407437 -1.263541
>
>
> 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: 0x600002ce0000>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM173bd185d8633"
[2] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM173bd24158ac4"
[3] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM173bd2495c5e"
[4] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM173bd1e4f207e"
[5] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM173bd5cde3fbd"
[6] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM173bd32ac0ed"
[7] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM173bd6be0093a"
[8] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM173bd417df62a"
[9] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM173bd34ac60fd"
[10] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM173bd21139d0f"
[11] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM173bdeac54c0"
[12] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM173bd53f010c6"
[13] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM173bd35dd6237"
[14] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM173bd595b2481"
[15] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM173bd6eb9befb"
>
>
> ### 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: 0x600002ce0b40>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x600002ce0b40>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x600002ce0b40>
> rowMedians(tmp)
[1] -5.607050e-01 3.957987e-02 1.625090e-01 1.667971e-01 -3.647595e-02
[6] -1.405365e-01 3.281397e-01 -1.374469e-01 -4.005082e-01 -9.290919e-02
[11] -5.513732e-01 5.921941e-01 -2.822174e-02 4.120682e-01 8.836362e-02
[16] -8.394654e-02 -1.724807e-01 8.339579e-01 8.672701e-02 6.702214e-01
[21] 4.442430e-01 3.535801e-01 -4.024363e-02 -1.532451e-01 -5.806619e-01
[26] 1.924432e-01 5.108871e-01 -3.123500e-01 1.680777e-01 4.669974e-01
[31] -7.578358e-01 -2.509910e-01 -3.812873e-02 8.526291e-02 -6.661624e-01
[36] 1.066956e-01 3.581409e-01 7.098078e-01 -6.747584e-02 2.143359e-01
[41] -2.498578e-02 7.237432e-01 -4.649979e-01 2.888842e-01 2.244044e-02
[46] -2.793794e-01 -2.109156e-01 3.571549e-01 4.819147e-01 1.233394e-01
[51] -3.065744e-01 4.203868e-01 4.766400e-01 2.185889e-01 -2.779855e-02
[56] -3.504310e-02 -5.684507e-02 1.751556e-01 -2.447849e-01 -4.684017e-01
[61] 3.388412e-01 2.151742e-01 -3.476588e-02 2.378080e-01 2.854248e-01
[66] 7.420559e-01 6.743331e-01 5.749929e-02 -2.768570e-01 3.132278e-01
[71] -5.252488e-01 -6.755135e-02 -1.542024e-01 4.974862e-02 -4.898287e-03
[76] -5.280674e-02 1.473631e-01 -1.109017e-01 4.574409e-02 -2.664260e-01
[81] -1.243631e-01 1.347219e-01 -2.055137e-01 -1.494845e-01 -8.470237e-02
[86] 4.291336e-01 -5.389201e-01 4.633642e-01 -1.914321e-01 1.636110e-01
[91] 2.174305e-02 -2.709405e-02 2.756864e-02 2.914451e-01 -8.505031e-01
[96] -8.467177e-01 3.089131e-01 -2.988077e-01 3.282366e-01 -4.241899e-01
[101] -3.023412e-02 7.325112e-02 -1.984636e-01 2.296906e-01 -1.651937e-01
[106] 2.432836e-01 9.580509e-02 5.256772e-02 -1.567879e-01 3.530709e-02
[111] 1.628324e-01 -8.152048e-01 4.556097e-01 -2.023858e-01 4.970862e-02
[116] -5.173691e-02 -3.351715e-01 -1.599780e-01 2.246630e-01 -6.378779e-02
[121] -3.625948e-01 4.858027e-01 -7.742879e-02 3.622224e-01 1.374148e-01
[126] -2.175999e-01 1.576349e-01 4.409676e-01 1.274362e-01 1.238477e-01
[131] -4.235071e-02 3.086284e-02 -4.441120e-01 -3.888606e-01 1.071376e-01
[136] 4.503818e-01 -7.293663e-02 -1.932746e-02 1.012634e+00 -9.423153e-03
[141] -1.837961e-01 1.491954e-01 5.345761e-01 -2.618688e-01 1.833131e-01
[146] 2.798453e-01 9.354912e-02 -1.661156e-01 6.361953e-02 -1.722427e-01
[151] 1.782063e-01 4.740619e-01 9.274464e-01 1.742842e-01 1.039985e-01
[156] -8.702848e-02 -1.591410e-01 1.577902e-01 4.130675e-02 -2.356073e-01
[161] 6.321174e-02 -5.648698e-01 -9.811617e-02 -2.101391e-01 2.946261e-01
[166] 2.538414e-01 -1.781030e-01 -1.525385e-01 1.098274e-01 9.979870e-02
[171] 2.890267e-01 -2.136652e-01 -3.014337e-01 1.107364e-01 3.186437e-01
[176] -9.486049e-02 7.927186e-01 3.726337e-01 -3.853721e-01 -2.470119e-01
[181] -3.932080e-01 -2.215296e-02 -2.397867e-01 3.267539e-01 -5.302890e-01
[186] 9.420428e-03 -4.068743e-02 -3.494106e-01 -4.498229e-01 4.501810e-01
[191] -1.101949e-01 -3.735441e-01 -2.695736e-01 3.860180e-01 1.075145e-01
[196] 8.409511e-02 -6.156208e-02 4.356538e-01 2.935385e-01 -3.741169e-02
[201] 9.297998e-02 -4.655887e-01 -2.998124e-02 3.443586e-01 7.385224e-02
[206] 5.437037e-01 4.477400e-01 4.714744e-02 9.147015e-05 4.851552e-01
[211] -4.381613e-01 1.406357e-01 3.312745e-01 2.317552e-02 -8.517188e-01
[216] -2.925568e-01 5.337950e-01 -5.361299e-01 -2.176368e-02 -1.489110e-01
[221] -3.370485e-01 -6.658876e-01 -2.295457e-02 -4.591299e-01 1.879831e-01
[226] -2.293352e-01 3.996986e-01 5.758973e-01 1.401467e-01 3.740628e-01
>
> proc.time()
user system elapsed
0.603 3.196 3.868
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root"
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: 0x6000001c0000>
> .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: 0x6000001c0000>
> .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: 0x6000001c0000>
> .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: 0x6000001c0000>
> 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: 0x6000001d81e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000001d81e0>
> .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: 0x6000001d81e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000001d81e0>
> .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: 0x6000001d81e0>
> 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: 0x6000001d83c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000001d83c0>
> .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: 0x6000001d83c0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x6000001d83c0>
> .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: 0x6000001d83c0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x6000001d83c0>
> .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: 0x6000001d83c0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x6000001d83c0>
> .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: 0x6000001d83c0>
> 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: 0x6000001d85a0>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x6000001d85a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000001d85a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000001d85a0>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1755a560ce622" "BufferedMatrixFile1755a5931d2e5"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1755a560ce622" "BufferedMatrixFile1755a5931d2e5"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000001d8840>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000001d8840>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x6000001d8840>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x6000001d8840>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x6000001d8840>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x6000001d8840>
> .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: 0x6000001d8a20>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000001d8a20>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x6000001d8a20>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x6000001d8a20>
> 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: 0x6000001d8c00>
> .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: 0x6000001d8c00>
> rm(P)
>
> proc.time()
user system elapsed
0.106 0.031 0.134
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root"
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
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.108 0.020 0.127