Ben Bolstad
| Snapshot Date: 2025-10-24 13:45 -0400 (Fri, 24 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 2025-10-25 12:05 -0400 (Sat, 25 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" | 4901 |
| lconway | macOS 12.7.6 Monterey | x86_64 | 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root" | 4691 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root" | 4637 |
| taishan | Linux (openEuler 24.03 LTS) | aarch64 | 4.5.0 (2025-04-11) -- "How About a Twenty-Six" | 4658 |
| 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 257/2361 | 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 12.7.6 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 | NA | NA | ||||||||||
|
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: 2025-10-24 18:47:31 -0400 (Fri, 24 Oct 2025) |
| EndedAt: 2025-10-24 18:47:47 -0400 (Fri, 24 Oct 2025) |
| EllapsedTime: 16.2 seconds |
| RetCode: 0 |
| Status: WARNINGS |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 1 |
##############################################################################
##############################################################################
###
### 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
0.107 0.035 0.139
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 1056615 56.5 NA 634357 33.9
Vcells 891019 6.8 8388608 64.0 196608 2109489 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 24 18:47:40 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 24 18:47:40 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: 0x600003010000>
>
>
>
> 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 24 18:47:41 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 24 18:47:42 2025"
>
> ColMode(tmp2)
<pointer: 0x600003010000>
>
>
>
> ### 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,] 100.5961494 0.1015978 0.48844013 0.4740607
[2,] -0.2393286 -0.1022116 0.33111471 -0.3795374
[3,] -0.5599194 -1.0844059 -0.02998175 -0.4524102
[4,] -1.1605364 -2.7884437 0.97606667 -1.2593785
> 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,] 100.5961494 0.1015978 0.48844013 0.4740607
[2,] 0.2393286 0.1022116 0.33111471 0.3795374
[3,] 0.5599194 1.0844059 0.02998175 0.4524102
[4,] 1.1605364 2.7884437 0.97606667 1.2593785
> 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,] 10.0297632 0.3187441 0.6988849 0.6885206
[2,] 0.4892122 0.3197056 0.5754257 0.6160661
[3,] 0.7482776 1.0413481 0.1731524 0.6726145
[4,] 1.0772820 1.6698634 0.9879609 1.1222203
>
> 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,] 225.89378 28.28904 32.47729 32.35927
[2,] 30.13145 28.29927 31.08537 31.54020
[3,] 33.04270 36.49789 26.76151 32.17855
[4,] 36.93336 44.48708 35.85568 37.48158
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x600003004000>
> exp(tmp5)
<pointer: 0x600003004000>
> log(tmp5,2)
<pointer: 0x600003004000>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 470.1683
> Min(tmp5)
[1] 54.09846
> mean(tmp5)
[1] 72.63537
> Sum(tmp5)
[1] 14527.07
> Var(tmp5)
[1] 870.3966
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 90.09894 68.34309 72.27725 73.09911 68.81329 69.69320 69.20536 70.80446
[9] 70.58066 73.43830
> rowSums(tmp5)
[1] 1801.979 1366.862 1445.545 1461.982 1376.266 1393.864 1384.107 1416.089
[9] 1411.613 1468.766
> rowVars(tmp5)
[1] 8065.95453 58.55280 104.49441 99.76191 79.88835 67.07932
[7] 43.23253 23.73428 89.47888 97.77458
> rowSd(tmp5)
[1] 89.810659 7.651980 10.222251 9.988089 8.938028 8.190196 6.575145
[8] 4.871785 9.459328 9.888103
> rowMax(tmp5)
[1] 470.16831 82.76980 91.81266 92.59402 83.58975 81.85570 78.17170
[8] 79.08003 87.59851 89.69892
> rowMin(tmp5)
[1] 57.52263 55.04875 54.09846 58.55550 55.95444 54.32423 56.44597 62.23544
[9] 54.61828 55.34987
>
> colMeans(tmp5)
[1] 108.27271 70.95966 68.07434 71.46303 67.36286 71.51660 69.39739
[8] 73.12127 68.61256 71.27145 74.89857 76.61799 71.73667 69.79265
[15] 70.58065 68.24134 69.94553 70.06757 72.41917 68.35529
> colSums(tmp5)
[1] 1082.7271 709.5966 680.7434 714.6303 673.6286 715.1660 693.9739
[8] 731.2127 686.1256 712.7145 748.9857 766.1799 717.3667 697.9265
[15] 705.8065 682.4134 699.4553 700.6757 724.1917 683.5529
> colVars(tmp5)
[1] 16223.83030 90.24156 71.21226 49.70766 45.65559 37.99519
[7] 123.04354 68.69576 114.18085 65.49259 110.40006 106.45803
[13] 57.36842 66.37897 49.32071 93.10539 70.55481 41.35605
[19] 110.89190 51.30513
> colSd(tmp5)
[1] 127.372800 9.499556 8.438736 7.050366 6.756892 6.164023
[7] 11.092499 8.288291 10.685544 8.092749 10.507143 10.317850
[13] 7.574195 8.147329 7.022871 9.649113 8.399691 6.430867
[19] 10.530522 7.162760
> colMax(tmp5)
[1] 470.16831 92.59402 83.23833 86.00476 74.86687 85.04540 84.05450
[8] 84.85217 85.32208 83.60154 89.44090 89.69892 81.40691 83.15318
[15] 78.75376 91.81266 82.08207 76.78556 85.08941 81.09856
> colMin(tmp5)
[1] 57.60283 58.87993 55.70057 63.09384 54.32423 64.03163 54.09846 59.27892
[9] 55.86169 60.72945 55.04875 58.78449 57.32875 54.61828 61.00898 55.95444
[17] 60.74279 60.38297 55.34987 58.55550
>
>
> ### 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] 90.09894 68.34309 72.27725 73.09911 NA 69.69320 69.20536 70.80446
[9] 70.58066 73.43830
> rowSums(tmp5)
[1] 1801.979 1366.862 1445.545 1461.982 NA 1393.864 1384.107 1416.089
[9] 1411.613 1468.766
> rowVars(tmp5)
[1] 8065.95453 58.55280 104.49441 99.76191 78.44490 67.07932
[7] 43.23253 23.73428 89.47888 97.77458
> rowSd(tmp5)
[1] 89.810659 7.651980 10.222251 9.988089 8.856912 8.190196 6.575145
[8] 4.871785 9.459328 9.888103
> rowMax(tmp5)
[1] 470.16831 82.76980 91.81266 92.59402 NA 81.85570 78.17170
[8] 79.08003 87.59851 89.69892
> rowMin(tmp5)
[1] 57.52263 55.04875 54.09846 58.55550 NA 54.32423 56.44597 62.23544
[9] 54.61828 55.34987
>
> colMeans(tmp5)
[1] 108.27271 70.95966 68.07434 71.46303 67.36286 71.51660 69.39739
[8] 73.12127 68.61256 71.27145 74.89857 NA 71.73667 69.79265
[15] 70.58065 68.24134 69.94553 70.06757 72.41917 68.35529
> colSums(tmp5)
[1] 1082.7271 709.5966 680.7434 714.6303 673.6286 715.1660 693.9739
[8] 731.2127 686.1256 712.7145 748.9857 NA 717.3667 697.9265
[15] 705.8065 682.4134 699.4553 700.6757 724.1917 683.5529
> colVars(tmp5)
[1] 16223.83030 90.24156 71.21226 49.70766 45.65559 37.99519
[7] 123.04354 68.69576 114.18085 65.49259 110.40006 NA
[13] 57.36842 66.37897 49.32071 93.10539 70.55481 41.35605
[19] 110.89190 51.30513
> colSd(tmp5)
[1] 127.372800 9.499556 8.438736 7.050366 6.756892 6.164023
[7] 11.092499 8.288291 10.685544 8.092749 10.507143 NA
[13] 7.574195 8.147329 7.022871 9.649113 8.399691 6.430867
[19] 10.530522 7.162760
> colMax(tmp5)
[1] 470.16831 92.59402 83.23833 86.00476 74.86687 85.04540 84.05450
[8] 84.85217 85.32208 83.60154 89.44090 NA 81.40691 83.15318
[15] 78.75376 91.81266 82.08207 76.78556 85.08941 81.09856
> colMin(tmp5)
[1] 57.60283 58.87993 55.70057 63.09384 54.32423 64.03163 54.09846 59.27892
[9] 55.86169 60.72945 55.04875 NA 57.32875 54.61828 61.00898 55.95444
[17] 60.74279 60.38297 55.34987 58.55550
>
> Max(tmp5,na.rm=TRUE)
[1] 470.1683
> Min(tmp5,na.rm=TRUE)
[1] 54.09846
> mean(tmp5,na.rm=TRUE)
[1] 72.70497
> Sum(tmp5,na.rm=TRUE)
[1] 14468.29
> Var(tmp5,na.rm=TRUE)
[1] 873.8187
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.09894 68.34309 72.27725 73.09911 69.34112 69.69320 69.20536 70.80446
[9] 70.58066 73.43830
> rowSums(tmp5,na.rm=TRUE)
[1] 1801.979 1366.862 1445.545 1461.982 1317.481 1393.864 1384.107 1416.089
[9] 1411.613 1468.766
> rowVars(tmp5,na.rm=TRUE)
[1] 8065.95453 58.55280 104.49441 99.76191 78.44490 67.07932
[7] 43.23253 23.73428 89.47888 97.77458
> rowSd(tmp5,na.rm=TRUE)
[1] 89.810659 7.651980 10.222251 9.988089 8.856912 8.190196 6.575145
[8] 4.871785 9.459328 9.888103
> rowMax(tmp5,na.rm=TRUE)
[1] 470.16831 82.76980 91.81266 92.59402 83.58975 81.85570 78.17170
[8] 79.08003 87.59851 89.69892
> rowMin(tmp5,na.rm=TRUE)
[1] 57.52263 55.04875 54.09846 58.55550 55.95444 54.32423 56.44597 62.23544
[9] 54.61828 55.34987
>
> colMeans(tmp5,na.rm=TRUE)
[1] 108.27271 70.95966 68.07434 71.46303 67.36286 71.51660 69.39739
[8] 73.12127 68.61256 71.27145 74.89857 78.59949 71.73667 69.79265
[15] 70.58065 68.24134 69.94553 70.06757 72.41917 68.35529
> colSums(tmp5,na.rm=TRUE)
[1] 1082.7271 709.5966 680.7434 714.6303 673.6286 715.1660 693.9739
[8] 731.2127 686.1256 712.7145 748.9857 707.3954 717.3667 697.9265
[15] 705.8065 682.4134 699.4553 700.6757 724.1917 683.5529
> colVars(tmp5,na.rm=TRUE)
[1] 16223.83030 90.24156 71.21226 49.70766 45.65559 37.99519
[7] 123.04354 68.69576 114.18085 65.49259 110.40006 75.59394
[13] 57.36842 66.37897 49.32071 93.10539 70.55481 41.35605
[19] 110.89190 51.30513
> colSd(tmp5,na.rm=TRUE)
[1] 127.372800 9.499556 8.438736 7.050366 6.756892 6.164023
[7] 11.092499 8.288291 10.685544 8.092749 10.507143 8.694478
[13] 7.574195 8.147329 7.022871 9.649113 8.399691 6.430867
[19] 10.530522 7.162760
> colMax(tmp5,na.rm=TRUE)
[1] 470.16831 92.59402 83.23833 86.00476 74.86687 85.04540 84.05450
[8] 84.85217 85.32208 83.60154 89.44090 89.69892 81.40691 83.15318
[15] 78.75376 91.81266 82.08207 76.78556 85.08941 81.09856
> colMin(tmp5,na.rm=TRUE)
[1] 57.60283 58.87993 55.70057 63.09384 54.32423 64.03163 54.09846 59.27892
[9] 55.86169 60.72945 55.04875 62.58221 57.32875 54.61828 61.00898 55.95444
[17] 60.74279 60.38297 55.34987 58.55550
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.09894 68.34309 72.27725 73.09911 NaN 69.69320 69.20536 70.80446
[9] 70.58066 73.43830
> rowSums(tmp5,na.rm=TRUE)
[1] 1801.979 1366.862 1445.545 1461.982 0.000 1393.864 1384.107 1416.089
[9] 1411.613 1468.766
> rowVars(tmp5,na.rm=TRUE)
[1] 8065.95453 58.55280 104.49441 99.76191 NA 67.07932
[7] 43.23253 23.73428 89.47888 97.77458
> rowSd(tmp5,na.rm=TRUE)
[1] 89.810659 7.651980 10.222251 9.988089 NA 8.190196 6.575145
[8] 4.871785 9.459328 9.888103
> rowMax(tmp5,na.rm=TRUE)
[1] 470.16831 82.76980 91.81266 92.59402 NA 81.85570 78.17170
[8] 79.08003 87.59851 89.69892
> rowMin(tmp5,na.rm=TRUE)
[1] 57.52263 55.04875 54.09846 58.55550 NA 54.32423 56.44597 62.23544
[9] 54.61828 55.34987
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 113.22034 70.95841 68.86767 70.81064 67.33502 71.43058 70.65092
[8] 72.03059 67.94575 69.90275 74.52808 NaN 73.33755 69.87861
[15] 71.64417 69.60656 70.49182 70.81658 72.20591 66.93937
> colSums(tmp5,na.rm=TRUE)
[1] 1018.9831 638.6257 619.8091 637.2958 606.0152 642.8752 635.8583
[8] 648.2753 611.5118 629.1248 670.7527 0.0000 660.0379 628.9075
[15] 644.7975 626.4590 634.4264 637.3492 649.8532 602.4543
> colVars(tmp5,na.rm=TRUE)
[1] 17976.41971 101.52173 73.03334 51.13309 51.35382 42.66134
[7] 120.74657 63.89981 123.45131 52.60409 122.65586 NA
[13] 35.70779 74.59321 42.76123 83.77580 76.01677 40.21413
[19] 124.24173 35.16397
> colSd(tmp5,na.rm=TRUE)
[1] 134.076171 10.075799 8.545954 7.150740 7.166158 6.531565
[7] 10.988474 7.993736 11.110864 7.252868 11.075011 NA
[13] 5.975599 8.636736 6.539207 9.152912 8.718759 6.341461
[19] 11.146378 5.929922
> colMax(tmp5,na.rm=TRUE)
[1] 470.16831 92.59402 83.23833 86.00476 74.86687 85.04540 84.05450
[8] 84.85217 85.32208 83.60154 89.44090 -Inf 81.40691 83.15318
[15] 78.75376 91.81266 82.08207 76.78556 85.08941 78.14758
> colMin(tmp5,na.rm=TRUE)
[1] 57.60283 58.87993 55.70057 63.09384 54.32423 64.03163 54.09846 59.27892
[9] 55.86169 60.72945 55.04875 Inf 64.28361 54.61828 64.02949 58.60094
[17] 60.74279 60.38297 55.34987 58.55550
>
>
>
>
> 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] 203.1152 136.4460 318.2558 136.5965 211.1902 173.1351 341.5767 299.4643
[9] 116.0015 250.2746
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 203.1152 136.4460 318.2558 136.5965 211.1902 173.1351 341.5767 299.4643
[9] 116.0015 250.2746
>
>
>
> 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] 0.000000e+00 5.684342e-14 -8.526513e-14 8.526513e-14 -1.136868e-13
[6] -1.136868e-13 5.684342e-14 -2.842171e-14 2.842171e-14 -5.684342e-14
[11] 2.842171e-14 -5.684342e-14 -1.421085e-14 7.105427e-15 0.000000e+00
[16] 8.526513e-14 5.684342e-14 -1.136868e-13 -1.136868e-13 1.421085e-13
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
7 4
2 1
2 3
7 6
2 20
3 13
9 14
3 1
5 5
10 12
4 10
6 16
2 6
8 2
6 9
6 12
7 19
2 15
9 14
9 5
There were 50 or more warnings (use warnings() to see the first 50)
>
>
> ### now test 1 by n and n by 1 matrix
>
>
> err.tol <- 1e-12
>
> rm(tmp5)
>
> dataset1 <- rnorm(100)
> dataset2 <- rnorm(100)
>
> tmp <- createBufferedMatrix(1,100)
> tmp[1,] <- dataset1
>
> tmp2 <- createBufferedMatrix(100,1)
> tmp2[,1] <- dataset2
>
>
>
>
>
> Max(tmp)
[1] 1.953201
> Min(tmp)
[1] -2.809662
> mean(tmp)
[1] -0.03301412
> Sum(tmp)
[1] -3.301412
> Var(tmp)
[1] 0.9343147
>
> rowMeans(tmp)
[1] -0.03301412
> rowSums(tmp)
[1] -3.301412
> rowVars(tmp)
[1] 0.9343147
> rowSd(tmp)
[1] 0.9665996
> rowMax(tmp)
[1] 1.953201
> rowMin(tmp)
[1] -2.809662
>
> colMeans(tmp)
[1] -0.982035629 -0.883578666 1.516486131 -0.587990511 -1.098546089
[6] 0.259620030 0.760530604 1.619508812 -0.033121640 -1.707892727
[11] 1.764526981 0.897392191 0.525823146 1.521924810 1.842521449
[16] -0.334101890 -2.298976030 1.127923373 -0.274364380 0.525431101
[21] -0.008601624 -0.411789698 0.099360265 0.624912601 -1.226861871
[26] -0.538466479 0.558213084 -1.083189451 1.019753622 1.166532857
[31] 0.904743926 -0.112029473 -1.268406867 -0.593915367 0.730406471
[36] 0.823321228 -1.155671674 -1.606108877 -1.468609907 -0.941760965
[41] -0.561712940 -0.536654596 0.803834772 -1.414886869 0.756003252
[46] 1.953200651 -0.137656444 0.737709269 -1.570997715 0.491729286
[51] -0.679126021 -0.260713273 0.041869138 0.304936171 1.205823384
[56] 1.069402505 0.092762074 0.918603595 -0.364328777 0.359746781
[61] 0.521669867 -0.319718560 -1.435644968 1.254160515 -0.279490943
[66] -1.653268296 0.126916500 0.367450421 0.359832366 0.093562760
[71] -0.576207779 0.501770130 -0.209016442 0.470227382 -1.811132381
[76] -0.429072804 0.945293865 1.540705454 0.447338894 -0.188057331
[81] -0.869108849 -0.349952407 0.951910222 -0.110946159 -1.472005124
[86] 1.091937892 -0.761558347 -2.809661840 -0.234141056 -0.147442161
[91] 0.945270230 -0.303771218 -0.208873133 -0.426228832 0.626662385
[96] -0.023016497 -0.276301615 -0.415009899 -0.962155894 -0.156795660
> colSums(tmp)
[1] -0.982035629 -0.883578666 1.516486131 -0.587990511 -1.098546089
[6] 0.259620030 0.760530604 1.619508812 -0.033121640 -1.707892727
[11] 1.764526981 0.897392191 0.525823146 1.521924810 1.842521449
[16] -0.334101890 -2.298976030 1.127923373 -0.274364380 0.525431101
[21] -0.008601624 -0.411789698 0.099360265 0.624912601 -1.226861871
[26] -0.538466479 0.558213084 -1.083189451 1.019753622 1.166532857
[31] 0.904743926 -0.112029473 -1.268406867 -0.593915367 0.730406471
[36] 0.823321228 -1.155671674 -1.606108877 -1.468609907 -0.941760965
[41] -0.561712940 -0.536654596 0.803834772 -1.414886869 0.756003252
[46] 1.953200651 -0.137656444 0.737709269 -1.570997715 0.491729286
[51] -0.679126021 -0.260713273 0.041869138 0.304936171 1.205823384
[56] 1.069402505 0.092762074 0.918603595 -0.364328777 0.359746781
[61] 0.521669867 -0.319718560 -1.435644968 1.254160515 -0.279490943
[66] -1.653268296 0.126916500 0.367450421 0.359832366 0.093562760
[71] -0.576207779 0.501770130 -0.209016442 0.470227382 -1.811132381
[76] -0.429072804 0.945293865 1.540705454 0.447338894 -0.188057331
[81] -0.869108849 -0.349952407 0.951910222 -0.110946159 -1.472005124
[86] 1.091937892 -0.761558347 -2.809661840 -0.234141056 -0.147442161
[91] 0.945270230 -0.303771218 -0.208873133 -0.426228832 0.626662385
[96] -0.023016497 -0.276301615 -0.415009899 -0.962155894 -0.156795660
> 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] -0.982035629 -0.883578666 1.516486131 -0.587990511 -1.098546089
[6] 0.259620030 0.760530604 1.619508812 -0.033121640 -1.707892727
[11] 1.764526981 0.897392191 0.525823146 1.521924810 1.842521449
[16] -0.334101890 -2.298976030 1.127923373 -0.274364380 0.525431101
[21] -0.008601624 -0.411789698 0.099360265 0.624912601 -1.226861871
[26] -0.538466479 0.558213084 -1.083189451 1.019753622 1.166532857
[31] 0.904743926 -0.112029473 -1.268406867 -0.593915367 0.730406471
[36] 0.823321228 -1.155671674 -1.606108877 -1.468609907 -0.941760965
[41] -0.561712940 -0.536654596 0.803834772 -1.414886869 0.756003252
[46] 1.953200651 -0.137656444 0.737709269 -1.570997715 0.491729286
[51] -0.679126021 -0.260713273 0.041869138 0.304936171 1.205823384
[56] 1.069402505 0.092762074 0.918603595 -0.364328777 0.359746781
[61] 0.521669867 -0.319718560 -1.435644968 1.254160515 -0.279490943
[66] -1.653268296 0.126916500 0.367450421 0.359832366 0.093562760
[71] -0.576207779 0.501770130 -0.209016442 0.470227382 -1.811132381
[76] -0.429072804 0.945293865 1.540705454 0.447338894 -0.188057331
[81] -0.869108849 -0.349952407 0.951910222 -0.110946159 -1.472005124
[86] 1.091937892 -0.761558347 -2.809661840 -0.234141056 -0.147442161
[91] 0.945270230 -0.303771218 -0.208873133 -0.426228832 0.626662385
[96] -0.023016497 -0.276301615 -0.415009899 -0.962155894 -0.156795660
> colMin(tmp)
[1] -0.982035629 -0.883578666 1.516486131 -0.587990511 -1.098546089
[6] 0.259620030 0.760530604 1.619508812 -0.033121640 -1.707892727
[11] 1.764526981 0.897392191 0.525823146 1.521924810 1.842521449
[16] -0.334101890 -2.298976030 1.127923373 -0.274364380 0.525431101
[21] -0.008601624 -0.411789698 0.099360265 0.624912601 -1.226861871
[26] -0.538466479 0.558213084 -1.083189451 1.019753622 1.166532857
[31] 0.904743926 -0.112029473 -1.268406867 -0.593915367 0.730406471
[36] 0.823321228 -1.155671674 -1.606108877 -1.468609907 -0.941760965
[41] -0.561712940 -0.536654596 0.803834772 -1.414886869 0.756003252
[46] 1.953200651 -0.137656444 0.737709269 -1.570997715 0.491729286
[51] -0.679126021 -0.260713273 0.041869138 0.304936171 1.205823384
[56] 1.069402505 0.092762074 0.918603595 -0.364328777 0.359746781
[61] 0.521669867 -0.319718560 -1.435644968 1.254160515 -0.279490943
[66] -1.653268296 0.126916500 0.367450421 0.359832366 0.093562760
[71] -0.576207779 0.501770130 -0.209016442 0.470227382 -1.811132381
[76] -0.429072804 0.945293865 1.540705454 0.447338894 -0.188057331
[81] -0.869108849 -0.349952407 0.951910222 -0.110946159 -1.472005124
[86] 1.091937892 -0.761558347 -2.809661840 -0.234141056 -0.147442161
[91] 0.945270230 -0.303771218 -0.208873133 -0.426228832 0.626662385
[96] -0.023016497 -0.276301615 -0.415009899 -0.962155894 -0.156795660
> colMedians(tmp)
[1] -0.982035629 -0.883578666 1.516486131 -0.587990511 -1.098546089
[6] 0.259620030 0.760530604 1.619508812 -0.033121640 -1.707892727
[11] 1.764526981 0.897392191 0.525823146 1.521924810 1.842521449
[16] -0.334101890 -2.298976030 1.127923373 -0.274364380 0.525431101
[21] -0.008601624 -0.411789698 0.099360265 0.624912601 -1.226861871
[26] -0.538466479 0.558213084 -1.083189451 1.019753622 1.166532857
[31] 0.904743926 -0.112029473 -1.268406867 -0.593915367 0.730406471
[36] 0.823321228 -1.155671674 -1.606108877 -1.468609907 -0.941760965
[41] -0.561712940 -0.536654596 0.803834772 -1.414886869 0.756003252
[46] 1.953200651 -0.137656444 0.737709269 -1.570997715 0.491729286
[51] -0.679126021 -0.260713273 0.041869138 0.304936171 1.205823384
[56] 1.069402505 0.092762074 0.918603595 -0.364328777 0.359746781
[61] 0.521669867 -0.319718560 -1.435644968 1.254160515 -0.279490943
[66] -1.653268296 0.126916500 0.367450421 0.359832366 0.093562760
[71] -0.576207779 0.501770130 -0.209016442 0.470227382 -1.811132381
[76] -0.429072804 0.945293865 1.540705454 0.447338894 -0.188057331
[81] -0.869108849 -0.349952407 0.951910222 -0.110946159 -1.472005124
[86] 1.091937892 -0.761558347 -2.809661840 -0.234141056 -0.147442161
[91] 0.945270230 -0.303771218 -0.208873133 -0.426228832 0.626662385
[96] -0.023016497 -0.276301615 -0.415009899 -0.962155894 -0.156795660
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.9820356 -0.8835787 1.516486 -0.5879905 -1.098546 0.25962 0.7605306
[2,] -0.9820356 -0.8835787 1.516486 -0.5879905 -1.098546 0.25962 0.7605306
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 1.619509 -0.03312164 -1.707893 1.764527 0.8973922 0.5258231 1.521925
[2,] 1.619509 -0.03312164 -1.707893 1.764527 0.8973922 0.5258231 1.521925
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 1.842521 -0.3341019 -2.298976 1.127923 -0.2743644 0.5254311 -0.008601624
[2,] 1.842521 -0.3341019 -2.298976 1.127923 -0.2743644 0.5254311 -0.008601624
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.4117897 0.09936026 0.6249126 -1.226862 -0.5384665 0.5582131 -1.083189
[2,] -0.4117897 0.09936026 0.6249126 -1.226862 -0.5384665 0.5582131 -1.083189
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 1.019754 1.166533 0.9047439 -0.1120295 -1.268407 -0.5939154 0.7304065
[2,] 1.019754 1.166533 0.9047439 -0.1120295 -1.268407 -0.5939154 0.7304065
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 0.8233212 -1.155672 -1.606109 -1.46861 -0.941761 -0.5617129 -0.5366546
[2,] 0.8233212 -1.155672 -1.606109 -1.46861 -0.941761 -0.5617129 -0.5366546
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 0.8038348 -1.414887 0.7560033 1.953201 -0.1376564 0.7377093 -1.570998
[2,] 0.8038348 -1.414887 0.7560033 1.953201 -0.1376564 0.7377093 -1.570998
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 0.4917293 -0.679126 -0.2607133 0.04186914 0.3049362 1.205823 1.069403
[2,] 0.4917293 -0.679126 -0.2607133 0.04186914 0.3049362 1.205823 1.069403
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 0.09276207 0.9186036 -0.3643288 0.3597468 0.5216699 -0.3197186 -1.435645
[2,] 0.09276207 0.9186036 -0.3643288 0.3597468 0.5216699 -0.3197186 -1.435645
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 1.254161 -0.2794909 -1.653268 0.1269165 0.3674504 0.3598324 0.09356276
[2,] 1.254161 -0.2794909 -1.653268 0.1269165 0.3674504 0.3598324 0.09356276
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -0.5762078 0.5017701 -0.2090164 0.4702274 -1.811132 -0.4290728 0.9452939
[2,] -0.5762078 0.5017701 -0.2090164 0.4702274 -1.811132 -0.4290728 0.9452939
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 1.540705 0.4473389 -0.1880573 -0.8691088 -0.3499524 0.9519102 -0.1109462
[2,] 1.540705 0.4473389 -0.1880573 -0.8691088 -0.3499524 0.9519102 -0.1109462
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] -1.472005 1.091938 -0.7615583 -2.809662 -0.2341411 -0.1474422 0.9452702
[2,] -1.472005 1.091938 -0.7615583 -2.809662 -0.2341411 -0.1474422 0.9452702
[,92] [,93] [,94] [,95] [,96] [,97]
[1,] -0.3037712 -0.2088731 -0.4262288 0.6266624 -0.0230165 -0.2763016
[2,] -0.3037712 -0.2088731 -0.4262288 0.6266624 -0.0230165 -0.2763016
[,98] [,99] [,100]
[1,] -0.4150099 -0.9621559 -0.1567957
[2,] -0.4150099 -0.9621559 -0.1567957
>
>
> Max(tmp2)
[1] 2.057996
> Min(tmp2)
[1] -2.298272
> mean(tmp2)
[1] 0.07603265
> Sum(tmp2)
[1] 7.603265
> Var(tmp2)
[1] 0.8256735
>
> rowMeans(tmp2)
[1] -0.89844281 1.21803282 1.06598488 -0.62513436 0.36411391 0.57155273
[7] 0.23198220 -0.58811438 0.72973095 0.18261816 -0.29039351 0.88057550
[13] 0.99934837 -0.71939043 0.33810117 0.27692611 0.01990809 0.80373328
[19] 0.78706332 1.38034159 -0.23556077 -0.38087306 -0.54408793 -0.58543629
[25] 1.66136868 0.12557355 -0.65835958 -0.98603318 -1.20644758 -1.29545352
[31] -0.11909616 0.12595913 -1.31626112 0.30316056 -0.25989083 -0.07221527
[37] -0.15219797 -1.41957147 -1.55145934 0.43896305 0.13356977 0.54654991
[43] -0.58865444 -1.03569733 0.11550994 -0.41877704 1.83672793 0.41506233
[49] -0.06739722 0.46910372 0.96782744 -2.04326297 -0.66845827 1.25891230
[55] 0.12369839 -0.28742853 1.95012504 -0.65482553 0.79199988 -0.03823754
[61] 0.68459521 1.66166379 -0.51417589 1.13768558 -0.10264846 -1.50547110
[67] 0.05703891 0.70374429 0.44606957 0.26249441 2.05799555 1.36127064
[73] 0.68633767 -1.02998802 0.92163931 -0.09943386 -0.71070605 -1.64379551
[79] 0.36926232 1.34655348 0.09179338 0.43414862 1.74967428 -2.29827224
[85] -0.08391244 0.25549380 1.54924908 0.55906645 0.12332668 -0.17138038
[91] -1.80821799 -0.81081046 -0.27715083 -0.15258245 0.12394714 0.40639931
[97] -1.01631295 0.41861013 0.67252441 0.34057350
> rowSums(tmp2)
[1] -0.89844281 1.21803282 1.06598488 -0.62513436 0.36411391 0.57155273
[7] 0.23198220 -0.58811438 0.72973095 0.18261816 -0.29039351 0.88057550
[13] 0.99934837 -0.71939043 0.33810117 0.27692611 0.01990809 0.80373328
[19] 0.78706332 1.38034159 -0.23556077 -0.38087306 -0.54408793 -0.58543629
[25] 1.66136868 0.12557355 -0.65835958 -0.98603318 -1.20644758 -1.29545352
[31] -0.11909616 0.12595913 -1.31626112 0.30316056 -0.25989083 -0.07221527
[37] -0.15219797 -1.41957147 -1.55145934 0.43896305 0.13356977 0.54654991
[43] -0.58865444 -1.03569733 0.11550994 -0.41877704 1.83672793 0.41506233
[49] -0.06739722 0.46910372 0.96782744 -2.04326297 -0.66845827 1.25891230
[55] 0.12369839 -0.28742853 1.95012504 -0.65482553 0.79199988 -0.03823754
[61] 0.68459521 1.66166379 -0.51417589 1.13768558 -0.10264846 -1.50547110
[67] 0.05703891 0.70374429 0.44606957 0.26249441 2.05799555 1.36127064
[73] 0.68633767 -1.02998802 0.92163931 -0.09943386 -0.71070605 -1.64379551
[79] 0.36926232 1.34655348 0.09179338 0.43414862 1.74967428 -2.29827224
[85] -0.08391244 0.25549380 1.54924908 0.55906645 0.12332668 -0.17138038
[91] -1.80821799 -0.81081046 -0.27715083 -0.15258245 0.12394714 0.40639931
[97] -1.01631295 0.41861013 0.67252441 0.34057350
> 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] -0.89844281 1.21803282 1.06598488 -0.62513436 0.36411391 0.57155273
[7] 0.23198220 -0.58811438 0.72973095 0.18261816 -0.29039351 0.88057550
[13] 0.99934837 -0.71939043 0.33810117 0.27692611 0.01990809 0.80373328
[19] 0.78706332 1.38034159 -0.23556077 -0.38087306 -0.54408793 -0.58543629
[25] 1.66136868 0.12557355 -0.65835958 -0.98603318 -1.20644758 -1.29545352
[31] -0.11909616 0.12595913 -1.31626112 0.30316056 -0.25989083 -0.07221527
[37] -0.15219797 -1.41957147 -1.55145934 0.43896305 0.13356977 0.54654991
[43] -0.58865444 -1.03569733 0.11550994 -0.41877704 1.83672793 0.41506233
[49] -0.06739722 0.46910372 0.96782744 -2.04326297 -0.66845827 1.25891230
[55] 0.12369839 -0.28742853 1.95012504 -0.65482553 0.79199988 -0.03823754
[61] 0.68459521 1.66166379 -0.51417589 1.13768558 -0.10264846 -1.50547110
[67] 0.05703891 0.70374429 0.44606957 0.26249441 2.05799555 1.36127064
[73] 0.68633767 -1.02998802 0.92163931 -0.09943386 -0.71070605 -1.64379551
[79] 0.36926232 1.34655348 0.09179338 0.43414862 1.74967428 -2.29827224
[85] -0.08391244 0.25549380 1.54924908 0.55906645 0.12332668 -0.17138038
[91] -1.80821799 -0.81081046 -0.27715083 -0.15258245 0.12394714 0.40639931
[97] -1.01631295 0.41861013 0.67252441 0.34057350
> rowMin(tmp2)
[1] -0.89844281 1.21803282 1.06598488 -0.62513436 0.36411391 0.57155273
[7] 0.23198220 -0.58811438 0.72973095 0.18261816 -0.29039351 0.88057550
[13] 0.99934837 -0.71939043 0.33810117 0.27692611 0.01990809 0.80373328
[19] 0.78706332 1.38034159 -0.23556077 -0.38087306 -0.54408793 -0.58543629
[25] 1.66136868 0.12557355 -0.65835958 -0.98603318 -1.20644758 -1.29545352
[31] -0.11909616 0.12595913 -1.31626112 0.30316056 -0.25989083 -0.07221527
[37] -0.15219797 -1.41957147 -1.55145934 0.43896305 0.13356977 0.54654991
[43] -0.58865444 -1.03569733 0.11550994 -0.41877704 1.83672793 0.41506233
[49] -0.06739722 0.46910372 0.96782744 -2.04326297 -0.66845827 1.25891230
[55] 0.12369839 -0.28742853 1.95012504 -0.65482553 0.79199988 -0.03823754
[61] 0.68459521 1.66166379 -0.51417589 1.13768558 -0.10264846 -1.50547110
[67] 0.05703891 0.70374429 0.44606957 0.26249441 2.05799555 1.36127064
[73] 0.68633767 -1.02998802 0.92163931 -0.09943386 -0.71070605 -1.64379551
[79] 0.36926232 1.34655348 0.09179338 0.43414862 1.74967428 -2.29827224
[85] -0.08391244 0.25549380 1.54924908 0.55906645 0.12332668 -0.17138038
[91] -1.80821799 -0.81081046 -0.27715083 -0.15258245 0.12394714 0.40639931
[97] -1.01631295 0.41861013 0.67252441 0.34057350
>
> colMeans(tmp2)
[1] 0.07603265
> colSums(tmp2)
[1] 7.603265
> colVars(tmp2)
[1] 0.8256735
> colSd(tmp2)
[1] 0.9086658
> colMax(tmp2)
[1] 2.057996
> colMin(tmp2)
[1] -2.298272
> colMedians(tmp2)
[1] 0.1238228
> colRanges(tmp2)
[,1]
[1,] -2.298272
[2,] 2.057996
>
> 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] 2.0032823 -4.7857336 -0.8511249 4.4448447 0.4125005 3.7306054
[7] 1.3070283 -2.8833106 -0.1308688 0.2516110
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.0833956
[2,] -0.7986391
[3,] 0.1826581
[4,] 0.8715756
[5,] 2.2200868
>
> rowApply(tmp,sum)
[1] -0.6688005 -1.2210660 3.6178194 -0.1286006 -3.3298672 0.6742277
[7] 6.0106845 -2.9150762 -3.0081067 4.4676200
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 2 7 8 6 9 3 10 2 3 5
[2,] 3 2 1 1 3 9 4 10 10 1
[3,] 9 3 2 4 7 7 6 6 1 8
[4,] 6 9 9 10 4 2 7 8 7 6
[5,] 4 4 7 3 6 8 9 3 8 3
[6,] 1 10 10 5 10 5 2 4 6 10
[7,] 8 6 4 7 2 10 8 9 2 4
[8,] 5 8 3 8 5 1 1 1 9 2
[9,] 10 1 5 2 8 6 3 7 4 7
[10,] 7 5 6 9 1 4 5 5 5 9
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 2.72816295 2.07866217 3.68589174 -2.35840653 1.94236203 -0.05388393
[7] 1.20390933 0.64556134 0.49621752 3.83421718 -3.86406580 0.90884830
[13] 0.75918042 -4.55766564 0.48987421 0.52683209 -0.35572351 0.89369281
[19] 0.95698442 -2.40215572
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.94706587
[2,] -0.05359485
[3,] 0.31881464
[4,] 0.53266086
[5,] 2.87734816
>
> rowApply(tmp,sum)
[1] -6.325922 -4.605986 9.027894 7.276482 2.186027
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 5 16 20 7 11
[2,] 12 5 16 15 15
[3,] 7 19 18 17 16
[4,] 3 6 2 12 12
[5,] 17 8 15 8 17
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -0.94706587 0.1772938 -0.9282249 -1.5771687 0.57147790 0.7627618
[2,] 0.53266086 -0.8275304 0.8484456 -0.8021524 -0.54372249 0.4107708
[3,] 2.87734816 1.1138708 1.4441409 -0.7495233 0.85556115 0.5483513
[4,] -0.05359485 0.8140768 1.3268464 0.3165442 -0.03222744 -0.9961431
[5,] 0.31881464 0.8009511 0.9946838 0.4538937 1.09127291 -0.7796247
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -0.1337211 0.9933308 -1.9994147 0.3596106 -1.4181789 0.4652609
[2,] -0.2462605 -0.4945652 0.5767035 0.3218582 0.1512015 0.7501353
[3,] 1.5545705 -0.2541998 -0.5283344 0.3114520 -0.2523885 -1.5646067
[4,] -1.1458618 0.5530770 3.0230896 1.6835055 -0.3150345 1.8332567
[5,] 1.1751821 -0.1520814 -0.5758265 1.1577910 -2.0296653 -0.5751979
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.39798031 -0.7883651 0.53047237 0.54561221 -0.43320034 -1.9283740
[2,] -1.41817755 -2.2105051 0.06492029 0.07409485 -1.31138148 1.7390475
[3,] 1.35716384 -0.2955660 0.48034089 0.21488307 0.75328376 0.2266084
[4,] 0.08803773 -1.0024250 0.02830194 0.26150486 -0.08588571 0.7134749
[5,] 1.13013670 -0.2608045 -0.61416128 -0.56926290 0.72146027 0.1429359
[,19] [,20]
[1,] 0.7487826 -0.9288311
[2,] -0.5518421 -1.6696868
[3,] 0.3612023 0.5737355
[4,] 1.1402496 -0.8743105
[5,] -0.7414078 0.4969372
>
>
> 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
row1 -0.3866848 0.0006075727 -0.5112538 -0.4714843 0.3340168 -0.362206
col7 col8 col9 col10 col11 col12 col13
row1 0.5232918 -1.451336 -2.204604 -0.198306 -3.500699 -0.05203344 0.5570303
col14 col15 col16 col17 col18 col19 col20
row1 -1.490271 0.3337095 -0.02741122 0.7668572 0.5477 1.977854 0.3062066
> tmp[,"col10"]
col10
row1 -0.19830595
row2 2.06461306
row3 0.40633692
row4 0.60047836
row5 -0.02865372
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 -0.3866848 0.0006075727 -0.5112538 -0.4714843 0.3340168 -0.3622060
row5 0.4778659 0.8461199761 1.2760355 0.3938894 -0.4426996 -0.6049776
col7 col8 col9 col10 col11 col12 col13
row1 0.5232918 -1.451336 -2.204604 -0.19830595 -3.500699 -0.05203344 0.5570303
row5 -0.2522364 -0.362749 1.100870 -0.02865372 -1.241168 1.05606598 0.6496935
col14 col15 col16 col17 col18 col19 col20
row1 -1.4902707 0.3337095 -0.02741122 0.7668572 0.547700 1.9778545 0.30620661
row5 0.2683643 0.4263215 -0.53524338 0.0484520 1.044354 -0.6200545 -0.04255686
> tmp[,c("col6","col20")]
col6 col20
row1 -0.3622060 0.30620661
row2 -0.4963359 1.05822893
row3 -2.4103338 0.72254829
row4 1.9057231 0.13014050
row5 -0.6049776 -0.04255686
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.3622060 0.30620661
row5 -0.6049776 -0.04255686
>
>
>
>
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105)
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.55936 51.49144 51.21307 49.17411 49.80649 105.6417 51.87069 48.85038
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.85569 50.14807 50.20171 48.84496 49.86463 49.85595 49.99447 49.50341
col17 col18 col19 col20
row1 50.01664 50.17706 49.98651 105.1071
> tmp[,"col10"]
col10
row1 50.14807
row2 30.95872
row3 28.86502
row4 27.08546
row5 50.10441
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.55936 51.49144 51.21307 49.17411 49.80649 105.6417 51.87069 48.85038
row5 51.16230 50.64817 50.64494 50.92609 48.67977 105.7597 50.32978 51.71090
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.85569 50.14807 50.20171 48.84496 49.86463 49.85595 49.99447 49.50341
row5 50.17875 50.10441 50.65567 50.21897 49.00358 50.30253 49.97867 51.58451
col17 col18 col19 col20
row1 50.01664 50.17706 49.98651 105.1071
row5 49.94021 49.86512 48.69957 102.6112
> tmp[,c("col6","col20")]
col6 col20
row1 105.64166 105.10713
row2 75.72199 75.19664
row3 74.69281 73.81310
row4 75.79256 74.87392
row5 105.75969 102.61121
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.6417 105.1071
row5 105.7597 102.6112
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.6417 105.1071
row5 105.7597 102.6112
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -1.2782069
[2,] 0.6677130
[3,] -1.3280623
[4,] 1.1892328
[5,] -0.5202158
> tmp[,c("col17","col7")]
col17 col7
[1,] -2.052221483 0.9006893
[2,] 0.007026299 0.5116972
[3,] 2.032053627 0.2584339
[4,] 0.117882491 0.6551952
[5,] 1.166827608 0.1657140
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.5621429 1.6720862
[2,] 0.7618617 -1.1796686
[3,] -0.9802343 0.9686198
[4,] 0.8987855 1.5190550
[5,] 0.8054900 -0.8891623
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.5621429
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.5621429
[2,] 0.7618617
>
>
>
> 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 1.1175451 0.9206503 1.5879144 0.2907810 -0.8581944 -1.6910257
row1 -0.1266903 -0.5836545 -0.2454332 0.1772952 0.5032154 -0.3973668
[,7] [,8] [,9] [,10] [,11] [,12]
row3 0.20013872 0.7574094 -0.7271279 -0.6562553 0.8228837 0.3573943
row1 -0.01306197 1.6748796 -0.2882522 0.1406745 1.1954026 -0.1389038
[,13] [,14] [,15] [,16] [,17] [,18]
row3 -0.02021645 -0.5432074 -0.9324708 -0.02355819 1.1500748 -2.2220180
row1 -1.09221922 0.0946048 0.5460507 -0.57821491 -0.9404247 0.5577004
[,19] [,20]
row3 1.3237387 1.116682
row1 -0.7097258 1.314283
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -1.008266 -0.1263882 -0.3311038 -0.3414353 -1.049652 -0.5848447 -1.14987
[,8] [,9] [,10]
row2 1.002107 0.5641119 -1.50032
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.04578486 -0.09750679 0.5731904 0.2778264 0.4867715 -0.3406614 -0.1540146
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.3813256 0.8331116 1.261744 -1.014666 0.3701871 0.7206146 1.610074
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.921494 1.101756 -0.6088642 0.2418532 1.252185 1.994933
>
>
> 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: 0x600003000600>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1540d2881af13"
[2] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1540d5a0d1d2b"
[3] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1540d12f6203d"
[4] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1540d5cbe8e84"
[5] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1540d627eabad"
[6] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1540d6a391d5f"
[7] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1540d4bb77e74"
[8] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1540d7bcf1881"
[9] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1540d5951fca7"
[10] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1540d15a265c1"
[11] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1540d58c66cff"
[12] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1540d4b1e06e1"
[13] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1540d2055c44e"
[14] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1540d5ecaed77"
[15] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1540d5cac503f"
>
>
> ### 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: 0x60000300c180>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x60000300c180>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x60000300c180>
> rowMedians(tmp)
[1] -0.186941463 0.064577602 -0.184661939 -0.070486065 0.313329983
[6] 0.353000819 0.111460618 0.275762968 -0.408373128 0.284546479
[11] -0.669924733 -0.107107572 -0.331509183 0.553110795 0.538119197
[16] 0.175209059 -0.783299869 -0.211832712 -0.528096342 0.040835207
[21] 0.282875812 -0.325305394 0.270335456 0.409204637 0.180875711
[26] -1.041689635 0.300061835 0.313327595 -0.034039915 0.094469045
[31] -0.101045587 0.753768298 -0.269044397 0.052660618 -0.250709174
[36] 0.030871986 -0.215300937 -0.166993462 0.156979620 0.268363632
[41] -0.329116575 0.232051485 0.325917223 0.329328347 0.297703375
[46] -0.012724603 0.242247772 -0.494084503 0.136864962 -0.100754645
[51] 0.412572837 0.184850055 -0.300072827 0.184052588 -0.362403034
[56] -0.096469444 0.514104563 -0.025823724 0.175438149 -0.486494252
[61] 0.349794898 -0.427108524 0.416044359 0.205393037 0.136239123
[66] 0.535585572 -0.179388953 -0.421307458 -0.249739961 0.467159889
[71] -0.076526095 0.533066264 -0.115880991 -0.209681147 0.456908957
[76] -0.072055875 0.096010316 -0.061528532 0.038224194 0.198736694
[81] 0.173957810 -0.425343076 -0.132809448 -0.268867580 -0.283420815
[86] 0.022567982 0.005950719 0.538904554 0.438738077 0.053909360
[91] 0.649651457 -0.447173910 -0.069937582 0.320193574 0.028076241
[96] 0.086961257 0.623614598 0.022443166 -0.498526953 -0.307789964
[101] 0.366389602 -0.198261831 -0.108083265 -0.063782691 -0.094909316
[106] 0.372846929 0.732373487 0.373148038 -0.255929056 0.424135973
[111] 0.028125405 0.352853069 0.011626822 0.185174112 -0.755545436
[116] -0.096991033 0.183226697 0.197398410 -0.483207376 -0.117354967
[121] 0.154211380 -0.692614684 -0.007090879 0.063363682 0.169135856
[126] 0.252152456 -0.362871987 -0.695642951 -0.204911736 -0.141583149
[131] -0.078081224 0.404353626 -0.358629293 -0.264910164 -0.715352054
[136] 0.051126147 0.402233496 0.247359937 -0.122685530 0.285807581
[141] 0.665611348 0.016737550 0.091199158 -0.295577660 0.392197514
[146] 0.097934976 0.274764198 0.249512142 0.246106438 0.453063897
[151] 0.108831800 -0.550521319 0.302514087 -0.215540326 0.091509286
[156] -0.044961236 0.157619033 -0.205848836 0.464080780 -0.112448215
[161] 0.028296700 -0.156686364 0.403750651 -0.676310774 0.042349021
[166] -0.148504845 0.085346301 0.860884428 0.686826139 0.287265307
[171] 0.325478929 -0.007771036 -0.253642718 0.064182180 -0.037837453
[176] 0.302887646 -0.356604398 0.332190215 0.361998100 -0.289815253
[181] -0.224983163 0.023426888 -0.438424742 0.242084579 0.218241267
[186] 0.286229120 0.386492657 -0.347590816 0.271888160 0.377779595
[191] -0.180640292 0.155740659 -0.708894458 -0.104542508 -0.113217419
[196] -0.094349931 0.386235362 0.312289633 -0.671800634 0.033796899
[201] 0.289294043 0.082732038 -0.324874313 0.290968495 -0.110262191
[206] -0.128885444 0.145230295 0.201510138 0.589401358 -0.073997896
[211] -0.010586550 -0.266122536 -0.028056577 -0.254893312 0.174259889
[216] -0.169803080 -0.222963632 0.353393244 -0.377509163 1.021539082
[221] 0.314426876 0.287793103 0.176905322 0.604319338 0.044554689
[226] -0.611059144 -0.620923860 0.124688329 0.420258846 -0.087047065
>
> proc.time()
user system elapsed
0.630 2.923 3.710
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: 0x6000037f0660>
> .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: 0x6000037f0660>
> .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: 0x6000037f0660>
> .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: 0x6000037f0660>
> 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: 0x6000037f4000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000037f4000>
> .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: 0x6000037f4000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000037f4000>
> .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: 0x6000037f4000>
> 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: 0x6000037f4180>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000037f4180>
> .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: 0x6000037f4180>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x6000037f4180>
> .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: 0x6000037f4180>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x6000037f4180>
> .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: 0x6000037f4180>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x6000037f4180>
> .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: 0x6000037f4180>
> 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: 0x6000037f4360>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x6000037f4360>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000037f4360>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000037f4360>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1552517d40011" "BufferedMatrixFile155255f50684f"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1552517d40011" "BufferedMatrixFile155255f50684f"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000037f0de0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000037f0de0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x6000037f0de0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x6000037f0de0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x6000037f0de0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x6000037f0de0>
> .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: 0x6000037f0fc0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000037f0fc0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x6000037f0fc0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x6000037f0fc0>
> 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: 0x6000037f11a0>
> .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: 0x6000037f11a0>
> rm(P)
>
> proc.time()
user system elapsed
0.109 0.036 0.142
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 0.023 0.128