Ben Bolstad
| Snapshot Date: 2025-09-12 13:45 -0400 (Fri, 12 Sep 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 2025-09-13 12:03 -0400 (Sat, 13 Sep 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" | 4719 |
| lconway | macOS 12.7.1 Monterey | x86_64 | 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root" | 4538 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root" | 4522 |
| taishan | Linux (openEuler 24.03 LTS) | aarch64 | 4.5.0 (2025-04-11) -- "How About a Twenty-Six" | 4543 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
| Package 253/2327 | 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: 2025-09-12 19:37:11 -0400 (Fri, 12 Sep 2025) |
| EndedAt: 2025-09-12 19:38:03 -0400 (Fri, 12 Sep 2025) |
| EllapsedTime: 51.9 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: x86_64-apple-darwin20
* R was compiled by
Apple clang version 14.0.0 (clang-1400.0.29.202)
GNU Fortran (GCC) 14.2.0
* running under: macOS Monterey 12.7.6
* 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 14.0.0 (clang-1400.0.29.202)’
* 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-x86_64/Resources/library’
* installing *source* package ‘BufferedMatrix’ ...
** this is package ‘BufferedMatrix’ version ‘1.73.0’
** using staged installation
** libs
using C compiler: ‘Apple clang version 14.0.0 (clang-1400.0.29.202)’
using SDK: ‘MacOSX11.3.1.sdk’
clang -arch x86_64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/x86_64/include -fPIC -falign-functions=64 -Wall -g -O2 -c RBufferedMatrix.c -o RBufferedMatrix.o
clang -arch x86_64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/x86_64/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 x86_64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/x86_64/include -fPIC -falign-functions=64 -Wall -g -O2 -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
clang -arch x86_64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/x86_64/include -fPIC -falign-functions=64 -Wall -g -O2 -c init_package.c -o init_package.o
clang -arch x86_64 -dynamiclib -Wl,-headerpad_max_install_names -undefined dynamic_lookup -L/Library/Frameworks/R.framework/Resources/lib -L/opt/R/x86_64/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-x86_64/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: x86_64-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
0.360 0.166 0.535
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: x86_64-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 480848 25.7 1056620 56.5 NA 634462 33.9
Vcells 891079 6.8 8388608 64.0 98304 2108727 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 Sep 12 19:37:36 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 Sep 12 19:37:37 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: 0x60000297c300>
>
>
>
> 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 Sep 12 19:37:41 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 Sep 12 19:37:43 2025"
>
> ColMode(tmp2)
<pointer: 0x60000297c300>
>
>
>
> ### 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,] 98.1538562 0.1996289 0.74646549 -1.6986113
[2,] -0.7195211 0.2814573 0.03294259 0.5887308
[3,] -1.1058934 -0.7961109 -0.97077217 -0.9185978
[4,] 2.2976631 0.4848726 0.51234884 0.6030855
> 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 : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 98.1538562 0.1996289 0.74646549 1.6986113
[2,] 0.7195211 0.2814573 0.03294259 0.5887308
[3,] 1.1058934 0.7961109 0.97077217 0.9185978
[4,] 2.2976631 0.4848726 0.51234884 0.6030855
> 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 : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 9.9072628 0.4467985 0.8639823 1.3033078
[2,] 0.8482459 0.5305255 0.1815009 0.7672880
[3,] 1.0516147 0.8922505 0.9852777 0.9584351
[4,] 1.5158044 0.6963279 0.7157855 0.7765858
>
> 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 : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 222.22648 29.66761 34.38629 39.73169
[2,] 34.20198 30.58671 26.84795 33.26161
[3,] 36.62204 34.71862 35.82355 35.50295
[4,] 42.45571 32.44815 32.67020 33.36894
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x6000029580c0>
> exp(tmp5)
<pointer: 0x6000029580c0>
> log(tmp5,2)
<pointer: 0x6000029580c0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 462.5353
> Min(tmp5)
[1] 52.51861
> mean(tmp5)
[1] 73.26871
> Sum(tmp5)
[1] 14653.74
> Var(tmp5)
[1] 841.7098
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 92.66730 71.75655 70.99813 74.41812 71.61745 71.41784 73.40825 70.09937
[9] 69.08559 67.21854
> rowSums(tmp5)
[1] 1853.346 1435.131 1419.963 1488.362 1432.349 1428.357 1468.165 1401.987
[9] 1381.712 1344.371
> rowVars(tmp5)
[1] 7646.34070 76.50745 115.22320 52.84598 60.59342 53.21426
[7] 112.68834 63.48041 70.97193 84.58128
> rowSd(tmp5)
[1] 87.443357 8.746854 10.734207 7.269524 7.784178 7.294811 10.615477
[8] 7.967459 8.424484 9.196808
> rowMax(tmp5)
[1] 462.53531 81.80070 88.78541 89.65029 89.77953 83.70250 92.50212
[8] 85.37930 81.79405 94.04364
> rowMin(tmp5)
[1] 54.13826 52.51861 54.09880 64.41333 55.17950 57.63617 55.33800 58.67425
[9] 54.33554 57.23838
>
> colMeans(tmp5)
[1] 113.93156 62.99117 72.18492 73.52286 73.08034 70.18798 73.31284
[8] 74.97748 73.25387 68.39451 73.64017 70.64119 70.05092 68.12135
[15] 75.93433 73.95270 64.91727 67.76986 73.96821 70.54073
> colSums(tmp5)
[1] 1139.3156 629.9117 721.8492 735.2286 730.8034 701.8798 733.1284
[8] 749.7748 732.5387 683.9451 736.4017 706.4119 700.5092 681.2135
[15] 759.3433 739.5270 649.1727 677.6986 739.6821 705.4073
> colVars(tmp5)
[1] 15041.76010 22.70392 67.19646 83.41481 54.74136 62.26589
[7] 89.29805 84.69846 79.26265 91.21372 67.36151 25.16042
[13] 97.46654 59.43926 32.77323 109.90314 68.70475 115.82223
[19] 135.71521 48.99360
> colSd(tmp5)
[1] 122.644854 4.764863 8.197345 9.133171 7.398740 7.890874
[7] 9.449764 9.203176 8.902957 9.550588 8.207406 5.016017
[13] 9.872514 7.709686 5.724791 10.483470 8.288833 10.762073
[19] 11.649687 6.999543
> colMax(tmp5)
[1] 462.53531 72.26225 86.67684 92.50212 80.38495 82.68307 87.59162
[8] 85.70189 89.65029 85.37930 88.78541 77.77566 86.45233 80.93200
[15] 84.28301 89.77953 78.62520 81.55694 94.04364 81.79405
> colMin(tmp5)
[1] 65.33423 57.33309 55.88049 62.27512 55.17950 58.67425 57.23838 58.04208
[9] 62.74432 54.09880 63.49698 62.26130 55.33800 57.63617 66.97679 59.96224
[17] 54.13826 52.51861 55.07286 60.45262
>
>
> ### 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] NA 71.75655 70.99813 74.41812 71.61745 71.41784 73.40825 70.09937
[9] 69.08559 67.21854
> rowSums(tmp5)
[1] NA 1435.131 1419.963 1488.362 1432.349 1428.357 1468.165 1401.987
[9] 1381.712 1344.371
> rowVars(tmp5)
[1] 8063.08376 76.50745 115.22320 52.84598 60.59342 53.21426
[7] 112.68834 63.48041 70.97193 84.58128
> rowSd(tmp5)
[1] 89.794676 8.746854 10.734207 7.269524 7.784178 7.294811 10.615477
[8] 7.967459 8.424484 9.196808
> rowMax(tmp5)
[1] NA 81.80070 88.78541 89.65029 89.77953 83.70250 92.50212 85.37930
[9] 81.79405 94.04364
> rowMin(tmp5)
[1] NA 52.51861 54.09880 64.41333 55.17950 57.63617 55.33800 58.67425
[9] 54.33554 57.23838
>
> colMeans(tmp5)
[1] 113.93156 62.99117 72.18492 73.52286 73.08034 70.18798 73.31284
[8] 74.97748 73.25387 68.39451 73.64017 70.64119 70.05092 NA
[15] 75.93433 73.95270 64.91727 67.76986 73.96821 70.54073
> colSums(tmp5)
[1] 1139.3156 629.9117 721.8492 735.2286 730.8034 701.8798 733.1284
[8] 749.7748 732.5387 683.9451 736.4017 706.4119 700.5092 NA
[15] 759.3433 739.5270 649.1727 677.6986 739.6821 705.4073
> colVars(tmp5)
[1] 15041.76010 22.70392 67.19646 83.41481 54.74136 62.26589
[7] 89.29805 84.69846 79.26265 91.21372 67.36151 25.16042
[13] 97.46654 NA 32.77323 109.90314 68.70475 115.82223
[19] 135.71521 48.99360
> colSd(tmp5)
[1] 122.644854 4.764863 8.197345 9.133171 7.398740 7.890874
[7] 9.449764 9.203176 8.902957 9.550588 8.207406 5.016017
[13] 9.872514 NA 5.724791 10.483470 8.288833 10.762073
[19] 11.649687 6.999543
> colMax(tmp5)
[1] 462.53531 72.26225 86.67684 92.50212 80.38495 82.68307 87.59162
[8] 85.70189 89.65029 85.37930 88.78541 77.77566 86.45233 NA
[15] 84.28301 89.77953 78.62520 81.55694 94.04364 81.79405
> colMin(tmp5)
[1] 65.33423 57.33309 55.88049 62.27512 55.17950 58.67425 57.23838 58.04208
[9] 62.74432 54.09880 63.49698 62.26130 55.33800 NA 66.97679 59.96224
[17] 54.13826 52.51861 55.07286 60.45262
>
> Max(tmp5,na.rm=TRUE)
[1] 462.5353
> Min(tmp5,na.rm=TRUE)
[1] 52.51861
> mean(tmp5,na.rm=TRUE)
[1] 73.2302
> Sum(tmp5,na.rm=TRUE)
[1] 14572.81
> Var(tmp5,na.rm=TRUE)
[1] 845.6628
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 93.28495 71.75655 70.99813 74.41812 71.61745 71.41784 73.40825 70.09937
[9] 69.08559 67.21854
> rowSums(tmp5,na.rm=TRUE)
[1] 1772.414 1435.131 1419.963 1488.362 1432.349 1428.357 1468.165 1401.987
[9] 1381.712 1344.371
> rowVars(tmp5,na.rm=TRUE)
[1] 8063.08376 76.50745 115.22320 52.84598 60.59342 53.21426
[7] 112.68834 63.48041 70.97193 84.58128
> rowSd(tmp5,na.rm=TRUE)
[1] 89.794676 8.746854 10.734207 7.269524 7.784178 7.294811 10.615477
[8] 7.967459 8.424484 9.196808
> rowMax(tmp5,na.rm=TRUE)
[1] 462.53531 81.80070 88.78541 89.65029 89.77953 83.70250 92.50212
[8] 85.37930 81.79405 94.04364
> rowMin(tmp5,na.rm=TRUE)
[1] 54.13826 52.51861 54.09880 64.41333 55.17950 57.63617 55.33800 58.67425
[9] 54.33554 57.23838
>
> colMeans(tmp5,na.rm=TRUE)
[1] 113.93156 62.99117 72.18492 73.52286 73.08034 70.18798 73.31284
[8] 74.97748 73.25387 68.39451 73.64017 70.64119 70.05092 66.69794
[15] 75.93433 73.95270 64.91727 67.76986 73.96821 70.54073
> colSums(tmp5,na.rm=TRUE)
[1] 1139.3156 629.9117 721.8492 735.2286 730.8034 701.8798 733.1284
[8] 749.7748 732.5387 683.9451 736.4017 706.4119 700.5092 600.2815
[15] 759.3433 739.5270 649.1727 677.6986 739.6821 705.4073
> colVars(tmp5,na.rm=TRUE)
[1] 15041.76010 22.70392 67.19646 83.41481 54.74136 62.26589
[7] 89.29805 84.69846 79.26265 91.21372 67.36151 25.16042
[13] 97.46654 44.07573 32.77323 109.90314 68.70475 115.82223
[19] 135.71521 48.99360
> colSd(tmp5,na.rm=TRUE)
[1] 122.644854 4.764863 8.197345 9.133171 7.398740 7.890874
[7] 9.449764 9.203176 8.902957 9.550588 8.207406 5.016017
[13] 9.872514 6.638955 5.724791 10.483470 8.288833 10.762073
[19] 11.649687 6.999543
> colMax(tmp5,na.rm=TRUE)
[1] 462.53531 72.26225 86.67684 92.50212 80.38495 82.68307 87.59162
[8] 85.70189 89.65029 85.37930 88.78541 77.77566 86.45233 79.77974
[15] 84.28301 89.77953 78.62520 81.55694 94.04364 81.79405
> colMin(tmp5,na.rm=TRUE)
[1] 65.33423 57.33309 55.88049 62.27512 55.17950 58.67425 57.23838 58.04208
[9] 62.74432 54.09880 63.49698 62.26130 55.33800 57.63617 66.97679 59.96224
[17] 54.13826 52.51861 55.07286 60.45262
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] NaN 71.75655 70.99813 74.41812 71.61745 71.41784 73.40825 70.09937
[9] 69.08559 67.21854
> rowSums(tmp5,na.rm=TRUE)
[1] 0.000 1435.131 1419.963 1488.362 1432.349 1428.357 1468.165 1401.987
[9] 1381.712 1344.371
> rowVars(tmp5,na.rm=TRUE)
[1] NA 76.50745 115.22320 52.84598 60.59342 53.21426 112.68834
[8] 63.48041 70.97193 84.58128
> rowSd(tmp5,na.rm=TRUE)
[1] NA 8.746854 10.734207 7.269524 7.784178 7.294811 10.615477
[8] 7.967459 8.424484 9.196808
> rowMax(tmp5,na.rm=TRUE)
[1] NA 81.80070 88.78541 89.65029 89.77953 83.70250 92.50212 85.37930
[9] 81.79405 94.04364
> rowMin(tmp5,na.rm=TRUE)
[1] NA 52.51861 54.09880 64.41333 55.17950 57.63617 55.33800 58.67425
[9] 54.33554 57.23838
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 75.19780 63.12917 72.25319 72.50358 72.85483 68.79963 73.19890 75.88341
[9] 72.84891 69.24917 73.52551 69.94041 68.87913 NaN 75.00669 74.95282
[17] 66.11494 66.40074 74.14645 70.68306
> colSums(tmp5,na.rm=TRUE)
[1] 676.7802 568.1625 650.2787 652.5322 655.6935 619.1967 658.7901 682.9507
[9] 655.6402 623.2425 661.7296 629.4637 619.9122 0.0000 675.0603 674.5754
[17] 595.0345 597.6066 667.3180 636.1476
> colVars(tmp5,na.rm=TRUE)
[1] 43.56640 25.32769 75.54359 82.15386 61.01192 48.36477 100.31424
[8] 86.05283 87.32550 94.39788 75.63379 22.78067 94.20251 NA
[15] 27.18925 112.38822 61.15576 109.21193 152.32220 54.88989
> colSd(tmp5,na.rm=TRUE)
[1] 6.600485 5.032662 8.691582 9.063877 7.811013 6.954479 10.015700
[8] 9.276466 9.344812 9.715857 8.696769 4.772910 9.705798 NA
[15] 5.214331 10.601331 7.820215 10.450451 12.341888 7.408771
> colMax(tmp5,na.rm=TRUE)
[1] 88.36599 72.26225 86.67684 92.50212 80.38495 77.16766 87.59162 85.70189
[9] 89.65029 85.37930 88.78541 77.77566 86.45233 -Inf 81.80070 89.77953
[17] 78.62520 81.55694 94.04364 81.79405
> colMin(tmp5,na.rm=TRUE)
[1] 65.33423 57.33309 55.88049 62.27512 55.17950 58.67425 57.23838 58.04208
[9] 62.74432 54.09880 63.49698 62.26130 55.33800 Inf 66.97679 59.96224
[17] 54.33554 52.51861 55.07286 60.45262
>
>
>
>
> 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] 329.4293 115.1673 252.5531 292.5988 118.1818 163.8868 180.2051 159.9146
[9] 282.8204 188.6872
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 329.4293 115.1673 252.5531 292.5988 118.1818 163.8868 180.2051 159.9146
[9] 282.8204 188.6872
>
>
>
> 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 -2.842171e-14 0.000000e+00 -5.684342e-14 -1.705303e-13
[6] 1.421085e-14 0.000000e+00 0.000000e+00 5.684342e-14 1.421085e-13
[11] -1.421085e-13 -2.842171e-14 0.000000e+00 2.273737e-13 -5.684342e-14
[16] -1.705303e-13 5.684342e-14 -8.526513e-14 0.000000e+00 2.842171e-14
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
2 14
4 2
7 11
10 12
4 19
6 2
8 4
4 6
3 3
7 13
3 17
1 14
9 15
3 14
8 2
6 10
8 13
5 18
3 9
10 15
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] 1.73907
> Min(tmp)
[1] -3.096465
> mean(tmp)
[1] -0.07739237
> Sum(tmp)
[1] -7.739237
> Var(tmp)
[1] 1.033592
>
> rowMeans(tmp)
[1] -0.07739237
> rowSums(tmp)
[1] -7.739237
> rowVars(tmp)
[1] 1.033592
> rowSd(tmp)
[1] 1.016657
> rowMax(tmp)
[1] 1.73907
> rowMin(tmp)
[1] -3.096465
>
> colMeans(tmp)
[1] 0.6370744932 0.7022167649 0.1922732502 -0.2532261514 0.4504141928
[6] 0.8761902423 -2.1276120145 0.2312625637 1.7390704300 0.5671206593
[11] -1.5866709026 0.1360923036 -0.9314187422 0.5186300203 -1.8514317919
[16] -1.6227340243 0.8101756420 -1.0275673442 -0.6502332394 1.5401367359
[21] 1.7140391797 -1.8446801151 0.0949631686 0.6363471380 0.0004854572
[26] 0.1873476880 1.4005530928 -0.1056630725 0.5805746871 -0.4657482123
[31] -1.4654252367 -1.1176043775 -0.3662394030 0.5704848733 -0.5672855175
[36] -0.4308834926 -0.4302982526 1.5117344694 -1.1674540040 -1.8914273497
[41] 0.7154168881 -1.3384856299 1.5144464707 0.4549665225 -1.0923114538
[46] 0.5062647617 0.6552471082 1.5598640137 -1.4433304582 -0.3202553083
[51] -0.0925976761 -0.0710150357 -0.8438642449 -0.6038484890 -0.4885955286
[56] -0.2920212585 0.9762645525 1.2013569055 -0.1139164238 0.7100269438
[61] 0.7074493566 0.9881074944 -0.1662822332 -1.5625363449 1.1376523990
[66] 0.4395028093 0.2422288444 0.7207223800 0.0860300502 1.6694946507
[71] 1.3224533465 -1.3521351250 -0.6760428367 -0.5806286396 1.2855074630
[76] 1.4504176591 -1.8948736294 -1.1369026489 0.3301320353 0.1125496579
[81] 0.0320199110 -0.3767051949 1.6069011766 -0.5166274269 0.6950113126
[86] -0.7006667499 -3.0964645907 -1.0160813713 0.5134476824 -0.2009591769
[91] 0.0342769231 -1.0203522322 -0.8520785854 -0.6565040052 -1.0211677936
[96] -0.2043066142 0.3400897369 0.5111016942 -1.0805421273 -0.6396725820
> colSums(tmp)
[1] 0.6370744932 0.7022167649 0.1922732502 -0.2532261514 0.4504141928
[6] 0.8761902423 -2.1276120145 0.2312625637 1.7390704300 0.5671206593
[11] -1.5866709026 0.1360923036 -0.9314187422 0.5186300203 -1.8514317919
[16] -1.6227340243 0.8101756420 -1.0275673442 -0.6502332394 1.5401367359
[21] 1.7140391797 -1.8446801151 0.0949631686 0.6363471380 0.0004854572
[26] 0.1873476880 1.4005530928 -0.1056630725 0.5805746871 -0.4657482123
[31] -1.4654252367 -1.1176043775 -0.3662394030 0.5704848733 -0.5672855175
[36] -0.4308834926 -0.4302982526 1.5117344694 -1.1674540040 -1.8914273497
[41] 0.7154168881 -1.3384856299 1.5144464707 0.4549665225 -1.0923114538
[46] 0.5062647617 0.6552471082 1.5598640137 -1.4433304582 -0.3202553083
[51] -0.0925976761 -0.0710150357 -0.8438642449 -0.6038484890 -0.4885955286
[56] -0.2920212585 0.9762645525 1.2013569055 -0.1139164238 0.7100269438
[61] 0.7074493566 0.9881074944 -0.1662822332 -1.5625363449 1.1376523990
[66] 0.4395028093 0.2422288444 0.7207223800 0.0860300502 1.6694946507
[71] 1.3224533465 -1.3521351250 -0.6760428367 -0.5806286396 1.2855074630
[76] 1.4504176591 -1.8948736294 -1.1369026489 0.3301320353 0.1125496579
[81] 0.0320199110 -0.3767051949 1.6069011766 -0.5166274269 0.6950113126
[86] -0.7006667499 -3.0964645907 -1.0160813713 0.5134476824 -0.2009591769
[91] 0.0342769231 -1.0203522322 -0.8520785854 -0.6565040052 -1.0211677936
[96] -0.2043066142 0.3400897369 0.5111016942 -1.0805421273 -0.6396725820
> 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] 0.6370744932 0.7022167649 0.1922732502 -0.2532261514 0.4504141928
[6] 0.8761902423 -2.1276120145 0.2312625637 1.7390704300 0.5671206593
[11] -1.5866709026 0.1360923036 -0.9314187422 0.5186300203 -1.8514317919
[16] -1.6227340243 0.8101756420 -1.0275673442 -0.6502332394 1.5401367359
[21] 1.7140391797 -1.8446801151 0.0949631686 0.6363471380 0.0004854572
[26] 0.1873476880 1.4005530928 -0.1056630725 0.5805746871 -0.4657482123
[31] -1.4654252367 -1.1176043775 -0.3662394030 0.5704848733 -0.5672855175
[36] -0.4308834926 -0.4302982526 1.5117344694 -1.1674540040 -1.8914273497
[41] 0.7154168881 -1.3384856299 1.5144464707 0.4549665225 -1.0923114538
[46] 0.5062647617 0.6552471082 1.5598640137 -1.4433304582 -0.3202553083
[51] -0.0925976761 -0.0710150357 -0.8438642449 -0.6038484890 -0.4885955286
[56] -0.2920212585 0.9762645525 1.2013569055 -0.1139164238 0.7100269438
[61] 0.7074493566 0.9881074944 -0.1662822332 -1.5625363449 1.1376523990
[66] 0.4395028093 0.2422288444 0.7207223800 0.0860300502 1.6694946507
[71] 1.3224533465 -1.3521351250 -0.6760428367 -0.5806286396 1.2855074630
[76] 1.4504176591 -1.8948736294 -1.1369026489 0.3301320353 0.1125496579
[81] 0.0320199110 -0.3767051949 1.6069011766 -0.5166274269 0.6950113126
[86] -0.7006667499 -3.0964645907 -1.0160813713 0.5134476824 -0.2009591769
[91] 0.0342769231 -1.0203522322 -0.8520785854 -0.6565040052 -1.0211677936
[96] -0.2043066142 0.3400897369 0.5111016942 -1.0805421273 -0.6396725820
> colMin(tmp)
[1] 0.6370744932 0.7022167649 0.1922732502 -0.2532261514 0.4504141928
[6] 0.8761902423 -2.1276120145 0.2312625637 1.7390704300 0.5671206593
[11] -1.5866709026 0.1360923036 -0.9314187422 0.5186300203 -1.8514317919
[16] -1.6227340243 0.8101756420 -1.0275673442 -0.6502332394 1.5401367359
[21] 1.7140391797 -1.8446801151 0.0949631686 0.6363471380 0.0004854572
[26] 0.1873476880 1.4005530928 -0.1056630725 0.5805746871 -0.4657482123
[31] -1.4654252367 -1.1176043775 -0.3662394030 0.5704848733 -0.5672855175
[36] -0.4308834926 -0.4302982526 1.5117344694 -1.1674540040 -1.8914273497
[41] 0.7154168881 -1.3384856299 1.5144464707 0.4549665225 -1.0923114538
[46] 0.5062647617 0.6552471082 1.5598640137 -1.4433304582 -0.3202553083
[51] -0.0925976761 -0.0710150357 -0.8438642449 -0.6038484890 -0.4885955286
[56] -0.2920212585 0.9762645525 1.2013569055 -0.1139164238 0.7100269438
[61] 0.7074493566 0.9881074944 -0.1662822332 -1.5625363449 1.1376523990
[66] 0.4395028093 0.2422288444 0.7207223800 0.0860300502 1.6694946507
[71] 1.3224533465 -1.3521351250 -0.6760428367 -0.5806286396 1.2855074630
[76] 1.4504176591 -1.8948736294 -1.1369026489 0.3301320353 0.1125496579
[81] 0.0320199110 -0.3767051949 1.6069011766 -0.5166274269 0.6950113126
[86] -0.7006667499 -3.0964645907 -1.0160813713 0.5134476824 -0.2009591769
[91] 0.0342769231 -1.0203522322 -0.8520785854 -0.6565040052 -1.0211677936
[96] -0.2043066142 0.3400897369 0.5111016942 -1.0805421273 -0.6396725820
> colMedians(tmp)
[1] 0.6370744932 0.7022167649 0.1922732502 -0.2532261514 0.4504141928
[6] 0.8761902423 -2.1276120145 0.2312625637 1.7390704300 0.5671206593
[11] -1.5866709026 0.1360923036 -0.9314187422 0.5186300203 -1.8514317919
[16] -1.6227340243 0.8101756420 -1.0275673442 -0.6502332394 1.5401367359
[21] 1.7140391797 -1.8446801151 0.0949631686 0.6363471380 0.0004854572
[26] 0.1873476880 1.4005530928 -0.1056630725 0.5805746871 -0.4657482123
[31] -1.4654252367 -1.1176043775 -0.3662394030 0.5704848733 -0.5672855175
[36] -0.4308834926 -0.4302982526 1.5117344694 -1.1674540040 -1.8914273497
[41] 0.7154168881 -1.3384856299 1.5144464707 0.4549665225 -1.0923114538
[46] 0.5062647617 0.6552471082 1.5598640137 -1.4433304582 -0.3202553083
[51] -0.0925976761 -0.0710150357 -0.8438642449 -0.6038484890 -0.4885955286
[56] -0.2920212585 0.9762645525 1.2013569055 -0.1139164238 0.7100269438
[61] 0.7074493566 0.9881074944 -0.1662822332 -1.5625363449 1.1376523990
[66] 0.4395028093 0.2422288444 0.7207223800 0.0860300502 1.6694946507
[71] 1.3224533465 -1.3521351250 -0.6760428367 -0.5806286396 1.2855074630
[76] 1.4504176591 -1.8948736294 -1.1369026489 0.3301320353 0.1125496579
[81] 0.0320199110 -0.3767051949 1.6069011766 -0.5166274269 0.6950113126
[86] -0.7006667499 -3.0964645907 -1.0160813713 0.5134476824 -0.2009591769
[91] 0.0342769231 -1.0203522322 -0.8520785854 -0.6565040052 -1.0211677936
[96] -0.2043066142 0.3400897369 0.5111016942 -1.0805421273 -0.6396725820
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.6370745 0.7022168 0.1922733 -0.2532262 0.4504142 0.8761902 -2.127612
[2,] 0.6370745 0.7022168 0.1922733 -0.2532262 0.4504142 0.8761902 -2.127612
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.2312626 1.73907 0.5671207 -1.586671 0.1360923 -0.9314187 0.51863
[2,] 0.2312626 1.73907 0.5671207 -1.586671 0.1360923 -0.9314187 0.51863
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -1.851432 -1.622734 0.8101756 -1.027567 -0.6502332 1.540137 1.714039
[2,] -1.851432 -1.622734 0.8101756 -1.027567 -0.6502332 1.540137 1.714039
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -1.84468 0.09496317 0.6363471 0.0004854572 0.1873477 1.400553 -0.1056631
[2,] -1.84468 0.09496317 0.6363471 0.0004854572 0.1873477 1.400553 -0.1056631
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 0.5805747 -0.4657482 -1.465425 -1.117604 -0.3662394 0.5704849 -0.5672855
[2,] 0.5805747 -0.4657482 -1.465425 -1.117604 -0.3662394 0.5704849 -0.5672855
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -0.4308835 -0.4302983 1.511734 -1.167454 -1.891427 0.7154169 -1.338486
[2,] -0.4308835 -0.4302983 1.511734 -1.167454 -1.891427 0.7154169 -1.338486
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 1.514446 0.4549665 -1.092311 0.5062648 0.6552471 1.559864 -1.44333
[2,] 1.514446 0.4549665 -1.092311 0.5062648 0.6552471 1.559864 -1.44333
[,50] [,51] [,52] [,53] [,54] [,55]
[1,] -0.3202553 -0.09259768 -0.07101504 -0.8438642 -0.6038485 -0.4885955
[2,] -0.3202553 -0.09259768 -0.07101504 -0.8438642 -0.6038485 -0.4885955
[,56] [,57] [,58] [,59] [,60] [,61] [,62]
[1,] -0.2920213 0.9762646 1.201357 -0.1139164 0.7100269 0.7074494 0.9881075
[2,] -0.2920213 0.9762646 1.201357 -0.1139164 0.7100269 0.7074494 0.9881075
[,63] [,64] [,65] [,66] [,67] [,68] [,69]
[1,] -0.1662822 -1.562536 1.137652 0.4395028 0.2422288 0.7207224 0.08603005
[2,] -0.1662822 -1.562536 1.137652 0.4395028 0.2422288 0.7207224 0.08603005
[,70] [,71] [,72] [,73] [,74] [,75] [,76]
[1,] 1.669495 1.322453 -1.352135 -0.6760428 -0.5806286 1.285507 1.450418
[2,] 1.669495 1.322453 -1.352135 -0.6760428 -0.5806286 1.285507 1.450418
[,77] [,78] [,79] [,80] [,81] [,82] [,83]
[1,] -1.894874 -1.136903 0.330132 0.1125497 0.03201991 -0.3767052 1.606901
[2,] -1.894874 -1.136903 0.330132 0.1125497 0.03201991 -0.3767052 1.606901
[,84] [,85] [,86] [,87] [,88] [,89] [,90]
[1,] -0.5166274 0.6950113 -0.7006667 -3.096465 -1.016081 0.5134477 -0.2009592
[2,] -0.5166274 0.6950113 -0.7006667 -3.096465 -1.016081 0.5134477 -0.2009592
[,91] [,92] [,93] [,94] [,95] [,96] [,97]
[1,] 0.03427692 -1.020352 -0.8520786 -0.656504 -1.021168 -0.2043066 0.3400897
[2,] 0.03427692 -1.020352 -0.8520786 -0.656504 -1.021168 -0.2043066 0.3400897
[,98] [,99] [,100]
[1,] 0.5111017 -1.080542 -0.6396726
[2,] 0.5111017 -1.080542 -0.6396726
>
>
> Max(tmp2)
[1] 2.523721
> Min(tmp2)
[1] -2.252496
> mean(tmp2)
[1] -0.01835288
> Sum(tmp2)
[1] -1.835288
> Var(tmp2)
[1] 0.800897
>
> rowMeans(tmp2)
[1] -0.922242565 0.477892735 -0.122958774 0.804030563 0.549295030
[6] -1.451669317 -0.044872281 -1.133049318 0.141899441 -0.325220288
[11] -1.284498458 -0.404918545 -0.595349057 -0.117429868 -1.058524371
[16] -0.755383138 -0.450224056 0.394260347 0.963159064 -0.046228746
[21] -0.613753938 0.647722862 -0.721393572 0.114273307 0.466538169
[26] 0.047982047 0.180192488 0.397758315 -0.768570938 0.127408238
[31] 1.207827439 0.699675219 1.056309164 1.127495873 -1.012658827
[36] 0.775725260 -0.851827771 1.161312679 0.671474133 0.010490722
[41] -0.693576402 0.789570910 -1.888575417 0.338646981 -1.697081333
[46] -0.272579932 0.010445848 -0.462322606 -0.184349617 -0.252465829
[51] 0.637650332 0.101723436 0.619842197 -0.002713692 0.788658024
[56] -0.376954879 0.673161232 -1.523948327 0.055336833 -0.783668013
[61] 0.264786361 1.020294210 0.944415201 0.742371341 0.842371369
[66] -0.674713690 1.063001849 -1.051461111 0.758855713 -1.526171754
[71] 0.627311114 -1.410742984 0.849322143 -0.053439131 0.511756999
[76] -0.447072137 0.399925272 0.705491769 0.822133478 -1.732364376
[81] 2.523721050 1.378684493 0.137325928 -0.962248068 -1.044960217
[86] -0.449139222 -0.599801450 0.226995254 -0.303051400 0.703400918
[91] -0.028533335 0.191655737 -0.130334299 2.127110721 -0.992671176
[96] 1.123797633 -1.020843845 1.150516252 -2.252496225 -1.489237589
> rowSums(tmp2)
[1] -0.922242565 0.477892735 -0.122958774 0.804030563 0.549295030
[6] -1.451669317 -0.044872281 -1.133049318 0.141899441 -0.325220288
[11] -1.284498458 -0.404918545 -0.595349057 -0.117429868 -1.058524371
[16] -0.755383138 -0.450224056 0.394260347 0.963159064 -0.046228746
[21] -0.613753938 0.647722862 -0.721393572 0.114273307 0.466538169
[26] 0.047982047 0.180192488 0.397758315 -0.768570938 0.127408238
[31] 1.207827439 0.699675219 1.056309164 1.127495873 -1.012658827
[36] 0.775725260 -0.851827771 1.161312679 0.671474133 0.010490722
[41] -0.693576402 0.789570910 -1.888575417 0.338646981 -1.697081333
[46] -0.272579932 0.010445848 -0.462322606 -0.184349617 -0.252465829
[51] 0.637650332 0.101723436 0.619842197 -0.002713692 0.788658024
[56] -0.376954879 0.673161232 -1.523948327 0.055336833 -0.783668013
[61] 0.264786361 1.020294210 0.944415201 0.742371341 0.842371369
[66] -0.674713690 1.063001849 -1.051461111 0.758855713 -1.526171754
[71] 0.627311114 -1.410742984 0.849322143 -0.053439131 0.511756999
[76] -0.447072137 0.399925272 0.705491769 0.822133478 -1.732364376
[81] 2.523721050 1.378684493 0.137325928 -0.962248068 -1.044960217
[86] -0.449139222 -0.599801450 0.226995254 -0.303051400 0.703400918
[91] -0.028533335 0.191655737 -0.130334299 2.127110721 -0.992671176
[96] 1.123797633 -1.020843845 1.150516252 -2.252496225 -1.489237589
> 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] -0.922242565 0.477892735 -0.122958774 0.804030563 0.549295030
[6] -1.451669317 -0.044872281 -1.133049318 0.141899441 -0.325220288
[11] -1.284498458 -0.404918545 -0.595349057 -0.117429868 -1.058524371
[16] -0.755383138 -0.450224056 0.394260347 0.963159064 -0.046228746
[21] -0.613753938 0.647722862 -0.721393572 0.114273307 0.466538169
[26] 0.047982047 0.180192488 0.397758315 -0.768570938 0.127408238
[31] 1.207827439 0.699675219 1.056309164 1.127495873 -1.012658827
[36] 0.775725260 -0.851827771 1.161312679 0.671474133 0.010490722
[41] -0.693576402 0.789570910 -1.888575417 0.338646981 -1.697081333
[46] -0.272579932 0.010445848 -0.462322606 -0.184349617 -0.252465829
[51] 0.637650332 0.101723436 0.619842197 -0.002713692 0.788658024
[56] -0.376954879 0.673161232 -1.523948327 0.055336833 -0.783668013
[61] 0.264786361 1.020294210 0.944415201 0.742371341 0.842371369
[66] -0.674713690 1.063001849 -1.051461111 0.758855713 -1.526171754
[71] 0.627311114 -1.410742984 0.849322143 -0.053439131 0.511756999
[76] -0.447072137 0.399925272 0.705491769 0.822133478 -1.732364376
[81] 2.523721050 1.378684493 0.137325928 -0.962248068 -1.044960217
[86] -0.449139222 -0.599801450 0.226995254 -0.303051400 0.703400918
[91] -0.028533335 0.191655737 -0.130334299 2.127110721 -0.992671176
[96] 1.123797633 -1.020843845 1.150516252 -2.252496225 -1.489237589
> rowMin(tmp2)
[1] -0.922242565 0.477892735 -0.122958774 0.804030563 0.549295030
[6] -1.451669317 -0.044872281 -1.133049318 0.141899441 -0.325220288
[11] -1.284498458 -0.404918545 -0.595349057 -0.117429868 -1.058524371
[16] -0.755383138 -0.450224056 0.394260347 0.963159064 -0.046228746
[21] -0.613753938 0.647722862 -0.721393572 0.114273307 0.466538169
[26] 0.047982047 0.180192488 0.397758315 -0.768570938 0.127408238
[31] 1.207827439 0.699675219 1.056309164 1.127495873 -1.012658827
[36] 0.775725260 -0.851827771 1.161312679 0.671474133 0.010490722
[41] -0.693576402 0.789570910 -1.888575417 0.338646981 -1.697081333
[46] -0.272579932 0.010445848 -0.462322606 -0.184349617 -0.252465829
[51] 0.637650332 0.101723436 0.619842197 -0.002713692 0.788658024
[56] -0.376954879 0.673161232 -1.523948327 0.055336833 -0.783668013
[61] 0.264786361 1.020294210 0.944415201 0.742371341 0.842371369
[66] -0.674713690 1.063001849 -1.051461111 0.758855713 -1.526171754
[71] 0.627311114 -1.410742984 0.849322143 -0.053439131 0.511756999
[76] -0.447072137 0.399925272 0.705491769 0.822133478 -1.732364376
[81] 2.523721050 1.378684493 0.137325928 -0.962248068 -1.044960217
[86] -0.449139222 -0.599801450 0.226995254 -0.303051400 0.703400918
[91] -0.028533335 0.191655737 -0.130334299 2.127110721 -0.992671176
[96] 1.123797633 -1.020843845 1.150516252 -2.252496225 -1.489237589
>
> colMeans(tmp2)
[1] -0.01835288
> colSums(tmp2)
[1] -1.835288
> colVars(tmp2)
[1] 0.800897
> colSd(tmp2)
[1] 0.8949285
> colMax(tmp2)
[1] 2.523721
> colMin(tmp2)
[1] -2.252496
> colMedians(tmp2)
[1] 0.02923638
> colRanges(tmp2)
[,1]
[1,] -2.252496
[2,] 2.523721
>
> 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] 4.1089358 0.7099790 2.6062419 2.2852577 6.0481620 -0.4923464
[7] -3.9075763 -6.8036898 -2.0686632 1.0285627
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.5948379
[2,] -0.3421200
[3,] 0.5375660
[4,] 1.0124970
[5,] 1.4508804
>
> rowApply(tmp,sum)
[1] 0.04768128 5.25025534 1.27570702 4.23143729 -3.13635590 -0.19413366
[7] 5.74459910 -2.72466419 0.57306575 -7.55272868
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 10 7 10 7 6 4 4 6 4 10
[2,] 3 4 5 5 7 5 7 7 9 8
[3,] 6 10 4 9 3 9 5 9 1 2
[4,] 9 2 1 10 8 7 9 3 6 5
[5,] 7 9 6 8 9 10 6 2 10 3
[6,] 2 5 7 3 10 2 8 5 3 4
[7,] 1 8 3 6 5 6 1 8 5 1
[8,] 5 1 9 1 1 3 2 4 2 7
[9,] 4 6 2 2 4 8 3 10 8 6
[10,] 8 3 8 4 2 1 10 1 7 9
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 1.8918963 0.4047595 0.2253164 -1.6667014 -2.1723046 -0.8156633
[7] 0.5690926 -0.5681132 -1.9151401 2.6065838 5.2772969 -0.2330478
[13] -3.6105592 0.3783796 -3.3376260 1.9343566 0.9213503 1.3729024
[19] 2.9965817 -1.4460411
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.1996587
[2,] -0.1802212
[3,] 0.1686879
[4,] 0.6399563
[5,] 1.4631320
>
> rowApply(tmp,sum)
[1] -0.7927127 0.9956181 -1.7676287 -1.6164018 5.9944445
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 14 20 10 11 6
[2,] 17 9 12 2 13
[3,] 20 1 2 5 19
[4,] 3 4 6 20 11
[5,] 10 2 7 13 4
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.6399563 0.91775244 2.1142123 -1.153319 -0.1691756 -0.7790711
[2,] 1.4631320 0.03032180 -1.6271164 -1.205830 -1.3315513 0.5562728
[3,] -0.1996587 -0.05890763 -1.1335254 -0.717805 -0.4736544 0.9653808
[4,] 0.1686879 -1.26377755 -0.8146853 1.255651 0.2072880 -0.5879587
[5,] -0.1802212 0.77937048 1.6864312 0.154601 -0.4052113 -0.9702870
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.6959099 0.9569735 -1.36855706 -0.03118688 1.4405281 0.40864368
[2,] -0.1184646 -1.2789280 -0.48633423 0.98039677 0.7773734 0.13360974
[3,] -0.4325163 -0.2509951 -0.02638924 1.16561611 0.4432057 -0.97956217
[4,] 0.7908873 -0.3530040 -1.13307219 -0.29841399 1.0640250 0.19148718
[5,] -0.3667237 0.3578404 1.09921261 0.79017179 1.5521648 0.01277377
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.66003523 0.7709278 -0.682538060 -1.9040595 -0.02548133 -0.5451932
[2,] -0.04534484 0.5207222 -0.007581705 0.3198930 1.04649287 0.6730845
[3,] -1.07506891 -0.1604879 -1.364680434 0.9956777 0.08867924 -0.7297492
[4,] -0.85285897 -0.6327216 0.390184205 1.2234531 -0.29953586 0.9035475
[5,] -0.97725123 -0.1200609 -1.673010001 1.2993924 0.11119534 1.0712128
[,19] [,20]
[1,] -0.7791018 -0.63989824
[2,] 0.1015067 0.49396350
[3,] 1.4767658 0.70004634
[4,] 0.3503774 -1.92596237
[5,] 1.8470336 -0.07419029
>
>
> 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 : 650 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 : 562 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 0.4125219 0.8535424 1.177726 0.9931577 0.5990013 -0.836175 -0.4374634
col8 col9 col10 col11 col12 col13 col14
row1 1.659619 0.2155756 2.060149 -1.827222 -1.940404 -0.02836746 -1.5964
col15 col16 col17 col18 col19 col20
row1 -1.192766 -2.633823 1.128106 2.261933 -1.619693 0.1331727
> tmp[,"col10"]
col10
row1 2.06014889
row2 -1.50998887
row3 0.01446502
row4 0.31460267
row5 0.59905652
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 0.41252192 0.85354238 1.1777255 0.9931577 0.5990013 -0.83617505
row5 -0.06908063 0.05761607 -0.4132967 1.2217229 -1.0745903 0.02678068
col7 col8 col9 col10 col11 col12
row1 -0.4374634 1.6596186 0.2155756 2.0601489 -1.8272218 -1.9404043
row5 -0.4691633 -0.5480973 0.1960047 0.5990565 -0.8640523 -0.7366231
col13 col14 col15 col16 col17 col18 col19
row1 -0.02836746 -1.596400 -1.192766 -2.6338230 1.128106 2.2619331 -1.6196930
row5 1.59729695 1.235372 -2.052063 0.1428183 1.595220 0.7066395 -0.2887265
col20
row1 0.1331727
row5 1.1953357
> tmp[,c("col6","col20")]
col6 col20
row1 -0.83617505 0.1331727
row2 1.41224759 0.2396087
row3 0.83050891 1.4457046
row4 -0.43801059 -0.9262264
row5 0.02678068 1.1953357
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.83617505 0.1331727
row5 0.02678068 1.1953357
>
>
>
>
> 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 50.56126 48.69764 52.17859 50.69674 48.77512 105.7443 51.24183 47.52662
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.06312 48.81179 50.61265 50.09132 49.54071 49.67994 51.42748 49.55809
col17 col18 col19 col20
row1 52.24395 49.68422 50.0468 105.4575
> tmp[,"col10"]
col10
row1 48.81179
row2 29.40899
row3 30.41880
row4 28.61329
row5 49.73588
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.56126 48.69764 52.17859 50.69674 48.77512 105.7443 51.24183 47.52662
row5 48.53591 48.35876 48.39438 49.99490 49.35867 103.9064 51.55495 50.25531
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.06312 48.81179 50.61265 50.09132 49.54071 49.67994 51.42748 49.55809
row5 48.90269 49.73588 49.42705 48.44574 50.90089 49.88316 49.31911 49.75934
col17 col18 col19 col20
row1 52.24395 49.68422 50.04680 105.4575
row5 51.31757 49.68663 49.67036 105.9701
> tmp[,c("col6","col20")]
col6 col20
row1 105.74432 105.45753
row2 75.17059 74.31288
row3 74.02760 75.95193
row4 76.15946 74.30682
row5 103.90643 105.97008
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.7443 105.4575
row5 103.9064 105.9701
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.7443 105.4575
row5 103.9064 105.9701
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 1.17805203
[2,] -0.39826873
[3,] -0.06488922
[4,] -0.13708791
[5,] -1.24748815
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.07033187 -0.80852485
[2,] -2.87704710 0.03452222
[3,] -0.51001691 0.89154396
[4,] -0.05706162 0.35357306
[5,] -0.19796717 0.89557501
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -1.3552809 0.9724436
[2,] 0.8324080 -1.2185535
[3,] -0.1750508 -0.3342730
[4,] -0.9041351 -0.5939975
[5,] -1.1669894 1.2812987
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -1.355281
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -1.355281
[2,] 0.832408
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row3 0.2657830 -0.4632905 -0.7855787 2.6520449 -0.3246793 0.678518 -1.466078
row1 0.2380839 -1.0229094 -1.8022568 0.6079245 -0.5386779 2.431605 -2.193044
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row3 1.6541480 -0.09450007 2.0527951 0.0904049 0.1347819 2.042621 0.487491
row1 0.6997922 1.90111787 -0.7000626 0.1885151 -1.0297285 -1.625053 1.347451
[,15] [,16] [,17] [,18] [,19] [,20]
row3 -1.303702 1.130865 -0.5725974 -0.7073184 -0.916851 -0.8909765
row1 0.114349 -2.286444 1.5873859 -1.0143273 1.270027 0.8130521
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.377645 1.569455 -1.163481 0.1108802 1.129449 1.704079 0.6805541
[,8] [,9] [,10]
row2 -1.081525 -0.4100726 0.01193561
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -1.313712 -0.4053955 -0.8788236 -0.3307418 0.6744239 2.510222 -1.535047
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.9882616 1.369846 -1.312852 0.2171355 -1.01191 -0.1478899 0.3739029
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.241876 0.02133246 -0.1341102 0.8405637 0.694792 -0.4261881
>
>
> 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: 0x6000029440c0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM55b3406d2a06"
[2] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM55b33ee210f5"
[3] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM55b36bc76513"
[4] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM55b36fbcf9ac"
[5] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM55b35fabc483"
[6] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM55b35f2a587"
[7] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM55b37d51451d"
[8] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM55b36290b331"
[9] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM55b39e48885"
[10] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM55b37abed8d5"
[11] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM55b378dc6e8"
[12] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM55b36cfdad37"
[13] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM55b32772dc8"
[14] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM55b35e5ea6bb"
[15] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM55b318146f64"
>
>
> ### 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: 0x600002914060>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x600002914060>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x600002914060>
> rowMedians(tmp)
[1] -0.590943772 -0.647211285 -0.168607184 0.173342269 0.452283796
[6] 0.287700267 0.410712948 -0.066537237 -0.117037846 0.258813612
[11] -0.368222239 0.126231373 0.425492660 0.285620595 -0.260488962
[16] -0.017816395 0.276886496 0.093214456 0.013765306 0.092841334
[21] -0.168674964 -0.099043747 -0.554137837 0.352786374 -0.324021632
[26] -0.641741038 0.278934683 -0.364153993 -0.101220966 -0.064600752
[31] -0.152025001 -0.103189445 -0.061732063 -0.395532924 0.218754449
[36] 0.084531699 -0.013147342 0.074739953 -0.497930982 0.360208704
[41] 0.267480124 -0.291126268 0.508093441 -0.140347545 -0.226032867
[46] 0.125064860 -0.095201071 0.072571169 -0.497350171 -0.318965770
[51] -0.300090838 0.012867812 0.192876315 0.116201455 0.239613274
[56] 0.261646957 0.517150657 0.968307121 -0.335667515 -0.108384679
[61] 0.179904266 0.344062353 -0.307660971 0.258465654 -0.456092977
[66] -0.636483877 -0.403826116 0.022334712 -0.322745856 -0.484801579
[71] 0.075809492 -0.621507822 -0.142928023 0.002156222 -0.198846622
[76] 0.028890601 -0.084735652 -0.071118914 -0.427482359 0.332318024
[81] 0.355895790 0.179197754 0.301056624 0.552889625 0.239854493
[86] -0.373753964 0.072515331 0.062391083 0.039463619 0.071215763
[91] -0.623203412 -0.082910388 -0.929536114 0.523512542 0.004362495
[96] -0.086447327 -0.155294775 0.603484764 0.617060462 -0.268427106
[101] -0.106058593 -0.257158662 -0.077492428 0.617456382 -0.234306658
[106] -0.081483942 0.253487374 -0.118193042 0.494284070 -0.019518392
[111] 0.186369280 0.179589482 -0.486997777 -0.320431649 -0.363178363
[116] -0.152661788 0.261726718 0.399804634 -0.611098334 0.274332467
[121] 0.147404216 -0.455590821 -0.119938065 -0.109274397 -0.237685168
[126] -0.165957686 -0.001319616 -0.054639231 -0.155749420 0.309260235
[131] 0.223661261 -0.020318555 0.435959500 0.408010614 0.279402696
[136] -0.762436484 0.088139454 0.066560285 -0.267822374 -0.200404768
[141] -0.238947840 0.030015469 -0.034388838 0.034649402 0.172172377
[146] -0.181729187 -0.128990112 0.077274871 0.438056811 0.182907596
[151] -0.382397367 -0.191148871 0.030872234 0.362284364 0.022722293
[156] -0.459202030 -0.023935863 -0.298448177 0.250417415 -0.075847020
[161] 0.392236166 0.369095052 0.161922895 -0.263426870 0.053030709
[166] 0.035338584 -0.155119983 -0.326179744 0.099237999 0.266940768
[171] 0.013832222 0.337360434 0.162728199 0.104335288 -0.108504793
[176] -0.195535460 -0.366735870 -0.133529521 0.510575545 0.366726526
[181] 0.411493136 0.125776758 0.008988136 0.143288813 -0.245387542
[186] 0.171908754 -0.536665146 0.159135794 0.554650419 0.183309434
[191] -0.283342346 -0.461060942 0.796606634 -0.056652464 -0.175635316
[196] -0.353866131 0.302975313 -0.264022100 0.116269327 0.140834981
[201] -0.067057179 -0.178402728 -0.102368924 -0.013618405 0.229672778
[206] 0.145995824 -0.173074461 0.374507267 -0.697410720 0.066025967
[211] -0.123344734 0.093578208 0.629173786 0.123153304 0.717077136
[216] 0.117550635 -0.304190499 -0.391272308 -0.110006816 0.044007474
[221] 0.219327981 0.064875862 -0.276732257 -0.583663334 0.561385220
[226] -0.211287324 -0.581294172 -0.017638827 0.031514283 0.476196980
>
> proc.time()
user system elapsed
2.594 15.057 18.135
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: x86_64-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: 0x6000033a8000>
> .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: 0x6000033a8000>
> .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: 0x6000033a8000>
> .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: 0x6000033a8000>
> 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: 0x6000033d8000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000033d8000>
> .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: 0x6000033d8000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000033d8000>
> .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: 0x6000033d8000>
> 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: 0x6000033c4000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000033c4000>
> .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: 0x6000033c4000>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x6000033c4000>
> .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: 0x6000033c4000>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x6000033c4000>
> .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: 0x6000033c4000>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x6000033c4000>
> .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: 0x6000033c4000>
> 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: 0x6000033c0000>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x6000033c0000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000033c0000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000033c0000>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile5c1627c6bcb8" "BufferedMatrixFile5c16688fe86e"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile5c1627c6bcb8" "BufferedMatrixFile5c16688fe86e"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000033cc120>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000033cc120>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x6000033cc120>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x6000033cc120>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x6000033cc120>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x6000033cc120>
> .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: 0x6000033cc300>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000033cc300>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x6000033cc300>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x6000033cc300>
> 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: 0x6000033b83c0>
> .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: 0x6000033b83c0>
> rm(P)
>
> proc.time()
user system elapsed
0.347 0.145 0.513
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: x86_64-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
0.369 0.101 0.466