Ben Bolstad
| Snapshot Date: 2025-10-03 13:45 -0400 (Fri, 03 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 2025-10-04 12:05 -0400 (Sat, 04 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" | 4853 |
| lconway | macOS 12.7.1 Monterey | x86_64 | 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root" | 4640 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root" | 4585 |
| taishan | Linux (openEuler 24.03 LTS) | aarch64 | 4.5.0 (2025-04-11) -- "How About a Twenty-Six" | 4576 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
| Package 255/2341 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.73.0 (landing page) Ben Bolstad
| nebbiolo2 | Linux (Ubuntu 24.04.3 LTS) / x86_64 | OK | OK | OK | | ||||||||
| lconway | macOS 12.7.1 Monterey / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| kjohnson3 | macOS 13.7.7 Ventura / arm64 | OK | OK | WARNINGS | OK | | ||||||||
| taishan | Linux (openEuler 24.03 LTS) / aarch64 | OK | OK | OK | ||||||||||
|
To the developers/maintainers of the BufferedMatrix package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/BufferedMatrix.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
| Package: BufferedMatrix |
| Version: 1.73.0 |
| Command: /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings BufferedMatrix_1.73.0.tar.gz |
| StartedAt: 2025-10-03 18:31:24 -0400 (Fri, 03 Oct 2025) |
| EndedAt: 2025-10-03 18:31:39 -0400 (Fri, 03 Oct 2025) |
| EllapsedTime: 15.2 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
0.108 0.032 0.137
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
>
> ### this is used to control how many repetitions in something below
> ### higher values result in more checks.
> nreps <-100 ##20000
>
>
> ## test creation and some simple assignments and subsetting operations
>
> ## first on single elements
> tmp <- createBufferedMatrix(1000,10)
>
> tmp[10,5]
[1] 0
> tmp[10,5] <- 10
> tmp[10,5]
[1] 10
> tmp[10,5] <- 12.445
> tmp[10,5]
[1] 12.445
>
>
>
> ## now testing accessing multiple elements
> tmp2 <- createBufferedMatrix(10,20)
>
>
> tmp2[3,1] <- 51.34
> tmp2[9,2] <- 9.87654
> tmp2[,1:2]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[,-(3:20)]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 51.34 0 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
> tmp2[-3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
[2,] 0 0 0 0 0 0 0
[3,] 0 0 0 0 0 0 0
[4,] 0 0 0 0 0 0 0
[5,] 0 0 0 0 0 0 0
[6,] 0 0 0 0 0 0 0
[7,] 0 0 0 0 0 0 0
[8,] 0 0 0 0 0 0 0
[9,] 0 0 0 0 0 0 0
> tmp2[2,1:3]
[,1] [,2] [,3]
[1,] 0 0 0
> tmp2[3:9,1:3]
[,1] [,2] [,3]
[1,] 51.34 0.00000 0
[2,] 0.00 0.00000 0
[3,] 0.00 0.00000 0
[4,] 0.00 0.00000 0
[5,] 0.00 0.00000 0
[6,] 0.00 0.00000 0
[7,] 0.00 9.87654 0
> tmp2[-4,-4]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 51.34 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0.00 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19]
[1,] 0 0 0 0 0 0
[2,] 0 0 0 0 0 0
[3,] 0 0 0 0 0 0
[4,] 0 0 0 0 0 0
[5,] 0 0 0 0 0 0
[6,] 0 0 0 0 0 0
[7,] 0 0 0 0 0 0
[8,] 0 0 0 0 0 0
[9,] 0 0 0 0 0 0
>
> ## now testing accessing/assigning multiple elements
> tmp3 <- createBufferedMatrix(10,10)
>
> for (i in 1:10){
+ for (j in 1:10){
+ tmp3[i,j] <- (j-1)*10 + i
+ }
+ }
>
> tmp3[2:4,2:4]
[,1] [,2] [,3]
[1,] 12 22 32
[2,] 13 23 33
[3,] 14 24 34
> tmp3[c(-10),c(2:4,2:4,10,1,2,1:10,10:1)]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 11 21 31 11 21 31 91 1 11 1 11 21 31
[2,] 12 22 32 12 22 32 92 2 12 2 12 22 32
[3,] 13 23 33 13 23 33 93 3 13 3 13 23 33
[4,] 14 24 34 14 24 34 94 4 14 4 14 24 34
[5,] 15 25 35 15 25 35 95 5 15 5 15 25 35
[6,] 16 26 36 16 26 36 96 6 16 6 16 26 36
[7,] 17 27 37 17 27 37 97 7 17 7 17 27 37
[8,] 18 28 38 18 28 38 98 8 18 8 18 28 38
[9,] 19 29 39 19 29 39 99 9 19 9 19 29 39
[,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25]
[1,] 41 51 61 71 81 91 91 81 71 61 51 41
[2,] 42 52 62 72 82 92 92 82 72 62 52 42
[3,] 43 53 63 73 83 93 93 83 73 63 53 43
[4,] 44 54 64 74 84 94 94 84 74 64 54 44
[5,] 45 55 65 75 85 95 95 85 75 65 55 45
[6,] 46 56 66 76 86 96 96 86 76 66 56 46
[7,] 47 57 67 77 87 97 97 87 77 67 57 47
[8,] 48 58 68 78 88 98 98 88 78 68 58 48
[9,] 49 59 69 79 89 99 99 89 79 69 59 49
[,26] [,27] [,28] [,29]
[1,] 31 21 11 1
[2,] 32 22 12 2
[3,] 33 23 13 3
[4,] 34 24 14 4
[5,] 35 25 15 5
[6,] 36 26 16 6
[7,] 37 27 17 7
[8,] 38 28 18 8
[9,] 39 29 19 9
> tmp3[-c(1:5),-c(6:10)]
[,1] [,2] [,3] [,4] [,5]
[1,] 6 16 26 36 46
[2,] 7 17 27 37 47
[3,] 8 18 28 38 48
[4,] 9 19 29 39 49
[5,] 10 20 30 40 50
>
> ## assignment of whole columns
> tmp3[,1] <- c(1:10*100.0)
> tmp3[,1:2] <- tmp3[,1:2]*100
> tmp3[,1:2] <- tmp3[,2:1]
> tmp3[,1:2]
[,1] [,2]
[1,] 1100 1e+04
[2,] 1200 2e+04
[3,] 1300 3e+04
[4,] 1400 4e+04
[5,] 1500 5e+04
[6,] 1600 6e+04
[7,] 1700 7e+04
[8,] 1800 8e+04
[9,] 1900 9e+04
[10,] 2000 1e+05
>
>
> tmp3[,-1] <- tmp3[,1:9]
> tmp3[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1100 1100 1e+04 21 31 41 51 61 71 81
[2,] 1200 1200 2e+04 22 32 42 52 62 72 82
[3,] 1300 1300 3e+04 23 33 43 53 63 73 83
[4,] 1400 1400 4e+04 24 34 44 54 64 74 84
[5,] 1500 1500 5e+04 25 35 45 55 65 75 85
[6,] 1600 1600 6e+04 26 36 46 56 66 76 86
[7,] 1700 1700 7e+04 27 37 47 57 67 77 87
[8,] 1800 1800 8e+04 28 38 48 58 68 78 88
[9,] 1900 1900 9e+04 29 39 49 59 69 79 89
[10,] 2000 2000 1e+05 30 40 50 60 70 80 90
>
> tmp3[,1:2] <- rep(1,10)
> tmp3[,1:2] <- rep(1,20)
> tmp3[,1:2] <- matrix(c(1:5),1,5)
>
> tmp3[,-c(1:8)] <- matrix(c(1:5),1,5)
>
> tmp3[1,] <- 1:10
> tmp3[1,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
> tmp3[-1,] <- c(1,2)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 2 1 2 1 2 1 2 1 2 1
[10,] 1 2 1 2 1 2 1 2 1 2
> tmp3[-c(1:8),] <- matrix(c(1:5),1,5)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 1 3 5 2 4 1 3 5 2 4
[10,] 2 4 1 3 5 2 4 1 3 5
>
>
> tmp3[1:2,1:2] <- 5555.04
> tmp3[-(1:2),1:2] <- 1234.56789
>
>
>
> ## testing accessors for the directory and prefix
> directory(tmp3)
[1] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests"
> prefix(tmp3)
[1] "BM"
>
> ## testing if we can remove these objects
> rm(tmp, tmp2, tmp3)
> gc()
used (Mb) gc trigger (Mb) limit (Mb) max used (Mb)
Ncells 480828 25.7 1056624 56.5 NA 634340 33.9
Vcells 891019 6.8 8388608 64.0 196608 2109889 16.1
>
>
>
>
> ##
> ## checking reads
> ##
>
> tmp2 <- createBufferedMatrix(10,20)
>
> test.sample <- rnorm(10*20)
>
> tmp2[1:10,1:20] <- test.sample
>
> test.matrix <- matrix(test.sample,10,20)
>
> ## testing reads
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Fri Oct 3 18:31:32 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 3 18:31:32 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: 0x6000024fcba0>
>
>
>
> 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 3 18:31:33 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 3 18:31:33 2025"
>
> ColMode(tmp2)
<pointer: 0x6000024fcba0>
>
>
>
> ### 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,] 99.8433503 -1.5786468 1.9141793 1.9075536
[2,] -0.1941510 -0.7311079 0.2613088 -0.4816849
[3,] -0.9676017 0.3384051 0.6577329 1.9439601
[4,] -0.8541350 0.7830303 -0.8657844 -0.2054543
> 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,] 99.8433503 1.5786468 1.9141793 1.9075536
[2,] 0.1941510 0.7311079 0.2613088 0.4816849
[3,] 0.9676017 0.3384051 0.6577329 1.9439601
[4,] 0.8541350 0.7830303 0.8657844 0.2054543
> 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,] 9.9921644 1.2564421 1.3835387 1.3811421
[2,] 0.4406257 0.8550485 0.5111837 0.6940352
[3,] 0.9836675 0.5817260 0.8110073 1.3942597
[4,] 0.9241943 0.8848900 0.9304754 0.4532707
>
> 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,] 224.76499 39.14307 40.74957 40.71897
[2,] 29.60041 34.28159 30.37315 32.42204
[3,] 35.80428 31.15566 33.76781 40.88656
[4,] 35.09608 34.63193 35.17054 29.73816
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x6000024f4300>
> exp(tmp5)
<pointer: 0x6000024f4300>
> log(tmp5,2)
<pointer: 0x6000024f4300>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 467.8189
> Min(tmp5)
[1] 53.41828
> mean(tmp5)
[1] 72.54693
> Sum(tmp5)
[1] 14509.39
> Var(tmp5)
[1] 871.1598
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 92.57953 68.33046 73.53562 70.56496 68.61151 69.30830 70.45539 69.61563
[9] 69.28830 73.17963
> rowSums(tmp5)
[1] 1851.591 1366.609 1470.712 1411.299 1372.230 1386.166 1409.108 1392.313
[9] 1385.766 1463.593
> rowVars(tmp5)
[1] 7885.61909 67.05779 118.41795 82.94814 92.41748 79.71323
[7] 72.73217 61.56413 93.13061 71.75569
> rowSd(tmp5)
[1] 88.801008 8.188882 10.882001 9.107587 9.613401 8.928226 8.528316
[8] 7.846281 9.650420 8.470873
> rowMax(tmp5)
[1] 467.81889 81.13814 99.28117 89.47486 87.01199 88.12077 92.06611
[8] 88.77680 86.62057 87.85161
> rowMin(tmp5)
[1] 56.43157 53.41828 60.58847 57.87264 54.44044 54.72743 55.12921 58.91765
[9] 54.26445 59.83353
>
> colMeans(tmp5)
[1] 112.99831 72.12060 72.92209 71.51932 70.46168 75.31443 68.01879
[8] 70.47459 64.43491 69.31654 65.38846 67.52109 71.03967 67.99109
[15] 72.21158 70.85347 73.46315 73.07407 69.47918 72.33564
> colSums(tmp5)
[1] 1129.9831 721.2060 729.2209 715.1932 704.6168 753.1443 680.1879
[8] 704.7459 644.3491 693.1654 653.8846 675.2109 710.3967 679.9109
[15] 722.1158 708.5347 734.6315 730.7407 694.7918 723.3564
> colVars(tmp5)
[1] 15631.38975 83.88142 52.91544 104.54685 55.62540 151.79296
[7] 40.40341 48.38874 74.79988 44.24569 89.21847 33.21635
[13] 74.20493 36.82295 183.10089 88.46849 177.17447 74.45172
[19] 70.82085 75.92896
> colSd(tmp5)
[1] 125.025556 9.158680 7.274300 10.224816 7.458244 12.320429
[7] 6.356368 6.956202 8.648693 6.651743 9.445553 5.763363
[13] 8.614229 6.068191 13.531478 9.405769 13.310690 8.628541
[19] 8.415513 8.713723
> colMax(tmp5)
[1] 467.81889 84.87075 84.81488 85.10001 85.86306 92.06611 80.56649
[8] 79.96293 85.44696 80.93933 78.27014 77.17101 84.95890 75.65963
[15] 99.28117 83.02366 94.89863 84.74642 81.13814 87.01199
> colMin(tmp5)
[1] 60.20739 54.72743 63.21772 55.12921 62.96591 57.02907 61.88083 58.98746
[9] 54.91537 58.79890 54.26445 61.77288 54.62074 56.89396 53.41828 54.98157
[17] 56.55213 58.40648 54.44044 61.11265
>
>
> ### 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] 92.57953 68.33046 73.53562 70.56496 68.61151 69.30830 70.45539 69.61563
[9] 69.28830 NA
> rowSums(tmp5)
[1] 1851.591 1366.609 1470.712 1411.299 1372.230 1386.166 1409.108 1392.313
[9] 1385.766 NA
> rowVars(tmp5)
[1] 7885.61909 67.05779 118.41795 82.94814 92.41748 79.71323
[7] 72.73217 61.56413 93.13061 75.47200
> rowSd(tmp5)
[1] 88.801008 8.188882 10.882001 9.107587 9.613401 8.928226 8.528316
[8] 7.846281 9.650420 8.687462
> rowMax(tmp5)
[1] 467.81889 81.13814 99.28117 89.47486 87.01199 88.12077 92.06611
[8] 88.77680 86.62057 NA
> rowMin(tmp5)
[1] 56.43157 53.41828 60.58847 57.87264 54.44044 54.72743 55.12921 58.91765
[9] 54.26445 NA
>
> colMeans(tmp5)
[1] 112.99831 72.12060 72.92209 NA 70.46168 75.31443 68.01879
[8] 70.47459 64.43491 69.31654 65.38846 67.52109 71.03967 67.99109
[15] 72.21158 70.85347 73.46315 73.07407 69.47918 72.33564
> colSums(tmp5)
[1] 1129.9831 721.2060 729.2209 NA 704.6168 753.1443 680.1879
[8] 704.7459 644.3491 693.1654 653.8846 675.2109 710.3967 679.9109
[15] 722.1158 708.5347 734.6315 730.7407 694.7918 723.3564
> colVars(tmp5)
[1] 15631.38975 83.88142 52.91544 NA 55.62540 151.79296
[7] 40.40341 48.38874 74.79988 44.24569 89.21847 33.21635
[13] 74.20493 36.82295 183.10089 88.46849 177.17447 74.45172
[19] 70.82085 75.92896
> colSd(tmp5)
[1] 125.025556 9.158680 7.274300 NA 7.458244 12.320429
[7] 6.356368 6.956202 8.648693 6.651743 9.445553 5.763363
[13] 8.614229 6.068191 13.531478 9.405769 13.310690 8.628541
[19] 8.415513 8.713723
> colMax(tmp5)
[1] 467.81889 84.87075 84.81488 NA 85.86306 92.06611 80.56649
[8] 79.96293 85.44696 80.93933 78.27014 77.17101 84.95890 75.65963
[15] 99.28117 83.02366 94.89863 84.74642 81.13814 87.01199
> colMin(tmp5)
[1] 60.20739 54.72743 63.21772 NA 62.96591 57.02907 61.88083 58.98746
[9] 54.91537 58.79890 54.26445 61.77288 54.62074 56.89396 53.41828 54.98157
[17] 56.55213 58.40648 54.44044 61.11265
>
> Max(tmp5,na.rm=TRUE)
[1] 467.8189
> Min(tmp5,na.rm=TRUE)
[1] 53.41828
> mean(tmp5,na.rm=TRUE)
[1] 72.55455
> Sum(tmp5,na.rm=TRUE)
[1] 14438.36
> Var(tmp5,na.rm=TRUE)
[1] 875.5479
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 92.57953 68.33046 73.53562 70.56496 68.61151 69.30830 70.45539 69.61563
[9] 69.28830 73.29275
> rowSums(tmp5,na.rm=TRUE)
[1] 1851.591 1366.609 1470.712 1411.299 1372.230 1386.166 1409.108 1392.313
[9] 1385.766 1392.562
> rowVars(tmp5,na.rm=TRUE)
[1] 7885.61909 67.05779 118.41795 82.94814 92.41748 79.71323
[7] 72.73217 61.56413 93.13061 75.47200
> rowSd(tmp5,na.rm=TRUE)
[1] 88.801008 8.188882 10.882001 9.107587 9.613401 8.928226 8.528316
[8] 7.846281 9.650420 8.687462
> rowMax(tmp5,na.rm=TRUE)
[1] 467.81889 81.13814 99.28117 89.47486 87.01199 88.12077 92.06611
[8] 88.77680 86.62057 87.85161
> rowMin(tmp5,na.rm=TRUE)
[1] 56.43157 53.41828 60.58847 57.87264 54.44044 54.72743 55.12921 58.91765
[9] 54.26445 59.83353
>
> colMeans(tmp5,na.rm=TRUE)
[1] 112.99831 72.12060 72.92209 71.57364 70.46168 75.31443 68.01879
[8] 70.47459 64.43491 69.31654 65.38846 67.52109 71.03967 67.99109
[15] 72.21158 70.85347 73.46315 73.07407 69.47918 72.33564
> colSums(tmp5,na.rm=TRUE)
[1] 1129.9831 721.2060 729.2209 644.1628 704.6168 753.1443 680.1879
[8] 704.7459 644.3491 693.1654 653.8846 675.2109 710.3967 679.9109
[15] 722.1158 708.5347 734.6315 730.7407 694.7918 723.3564
> colVars(tmp5,na.rm=TRUE)
[1] 15631.38975 83.88142 52.91544 117.58202 55.62540 151.79296
[7] 40.40341 48.38874 74.79988 44.24569 89.21847 33.21635
[13] 74.20493 36.82295 183.10089 88.46849 177.17447 74.45172
[19] 70.82085 75.92896
> colSd(tmp5,na.rm=TRUE)
[1] 125.025556 9.158680 7.274300 10.843524 7.458244 12.320429
[7] 6.356368 6.956202 8.648693 6.651743 9.445553 5.763363
[13] 8.614229 6.068191 13.531478 9.405769 13.310690 8.628541
[19] 8.415513 8.713723
> colMax(tmp5,na.rm=TRUE)
[1] 467.81889 84.87075 84.81488 85.10001 85.86306 92.06611 80.56649
[8] 79.96293 85.44696 80.93933 78.27014 77.17101 84.95890 75.65963
[15] 99.28117 83.02366 94.89863 84.74642 81.13814 87.01199
> colMin(tmp5,na.rm=TRUE)
[1] 60.20739 54.72743 63.21772 55.12921 62.96591 57.02907 61.88083 58.98746
[9] 54.91537 58.79890 54.26445 61.77288 54.62074 56.89396 53.41828 54.98157
[17] 56.55213 58.40648 54.44044 61.11265
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 92.57953 68.33046 73.53562 70.56496 68.61151 69.30830 70.45539 69.61563
[9] 69.28830 NaN
> rowSums(tmp5,na.rm=TRUE)
[1] 1851.591 1366.609 1470.712 1411.299 1372.230 1386.166 1409.108 1392.313
[9] 1385.766 0.000
> rowVars(tmp5,na.rm=TRUE)
[1] 7885.61909 67.05779 118.41795 82.94814 92.41748 79.71323
[7] 72.73217 61.56413 93.13061 NA
> rowSd(tmp5,na.rm=TRUE)
[1] 88.801008 8.188882 10.882001 9.107587 9.613401 8.928226 8.528316
[8] 7.846281 9.650420 NA
> rowMax(tmp5,na.rm=TRUE)
[1] 467.81889 81.13814 99.28117 89.47486 87.01199 88.12077 92.06611
[8] 88.77680 86.62057 NA
> rowMin(tmp5,na.rm=TRUE)
[1] 56.43157 53.41828 60.58847 57.87264 54.44044 54.72743 55.12921 58.91765
[9] 54.26445 NA
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 116.82148 71.35109 73.48874 NaN 68.75042 75.10359 68.69099
[8] 70.86336 64.58222 68.02512 66.00567 66.87441 69.49309 67.43278
[15] 72.33818 71.61565 71.86443 73.21112 68.20723 73.23943
> colSums(tmp5,na.rm=TRUE)
[1] 1051.3933 642.1599 661.3986 0.0000 618.7538 675.9323 618.2189
[8] 637.7703 581.2400 612.2261 594.0511 601.8697 625.4378 606.8951
[15] 651.0436 644.5409 646.7799 658.9001 613.8650 659.1549
> colVars(tmp5,na.rm=TRUE)
[1] 17420.87606 87.70504 55.91766 NA 29.63380 170.26699
[7] 40.37048 52.73698 83.90572 31.01401 96.08506 32.66380
[13] 56.57155 37.91919 205.80821 92.99162 170.56740 83.54689
[19] 61.47260 76.23072
> colSd(tmp5,na.rm=TRUE)
[1] 131.988166 9.365097 7.477811 NA 5.443694 13.048639
[7] 6.353777 7.262023 9.160006 5.569022 9.802299 5.715225
[13] 7.521406 6.157856 14.346017 9.643216 13.060145 9.140399
[19] 7.840446 8.731021
> colMax(tmp5,na.rm=TRUE)
[1] 467.81889 84.87075 84.81488 -Inf 79.70016 92.06611 80.56649
[8] 79.96293 85.44696 74.79513 78.27014 77.17101 78.18646 75.65963
[15] 99.28117 83.02366 94.89863 84.74642 81.13814 87.01199
> colMin(tmp5,na.rm=TRUE)
[1] 60.20739 54.72743 63.21772 Inf 62.96591 57.02907 61.88083 58.98746
[9] 54.91537 58.79890 54.26445 61.77288 54.62074 56.89396 53.41828 54.98157
[17] 56.55213 58.40648 54.44044 61.11265
>
>
>
>
> 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] 236.1647 271.8796 271.5846 243.3815 139.1656 280.8164 182.5721 126.5168
[9] 194.1746 260.3239
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 236.1647 271.8796 271.5846 243.3815 139.1656 280.8164 182.5721 126.5168
[9] 194.1746 260.3239
>
>
>
> 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 1.136868e-13 0.000000e+00 -5.684342e-14
[6] 0.000000e+00 7.105427e-14 8.526513e-14 -2.842171e-14 -1.136868e-13
[11] 0.000000e+00 0.000000e+00 1.136868e-13 9.947598e-14 -2.273737e-13
[16] 0.000000e+00 -1.705303e-13 -2.842171e-14 -1.421085e-14 -8.526513e-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)
+ }
4 10
5 18
8 11
2 11
2 12
8 6
1 16
1 12
9 14
6 10
4 14
1 11
6 2
7 7
6 19
7 13
7 9
5 2
5 20
2 12
There were 50 or more warnings (use warnings() to see the first 50)
>
>
> ### now test 1 by n and n by 1 matrix
>
>
> err.tol <- 1e-12
>
> rm(tmp5)
>
> dataset1 <- rnorm(100)
> dataset2 <- rnorm(100)
>
> tmp <- createBufferedMatrix(1,100)
> tmp[1,] <- dataset1
>
> tmp2 <- createBufferedMatrix(100,1)
> tmp2[,1] <- dataset2
>
>
>
>
>
> Max(tmp)
[1] 2.235438
> Min(tmp)
[1] -2.11324
> mean(tmp)
[1] -0.0001738499
> Sum(tmp)
[1] -0.01738499
> Var(tmp)
[1] 0.8981481
>
> rowMeans(tmp)
[1] -0.0001738499
> rowSums(tmp)
[1] -0.01738499
> rowVars(tmp)
[1] 0.8981481
> rowSd(tmp)
[1] 0.9477067
> rowMax(tmp)
[1] 2.235438
> rowMin(tmp)
[1] -2.11324
>
> colMeans(tmp)
[1] 0.516197123 0.611815049 -0.436061869 0.427490743 -1.159860654
[6] -1.578263034 -0.676145828 -0.254589536 -1.660160081 -0.699024733
[11] 0.112533507 0.427416303 -1.476449748 0.397234819 0.579652865
[16] -0.902140030 -0.004798942 -0.217807557 -0.454352721 0.689827025
[21] -1.529578649 0.489081862 0.078172342 0.178261007 -1.425520547
[26] 0.738468238 0.090104159 1.384170151 0.619310303 0.469156450
[31] 0.352380763 -0.734349480 2.235438276 0.344000288 1.115510253
[36] 1.091180037 0.949792286 -0.809301412 0.865388338 -0.268247338
[41] -0.188950949 -1.453456521 0.687822081 0.800685710 -0.469372967
[46] -0.722152436 -2.113239942 1.094459352 -1.312417668 0.452734588
[51] -0.373167462 1.396168523 1.391953754 0.060037255 -0.611852752
[56] 1.134564407 -0.889555180 0.195563790 -1.096946815 -0.330332268
[61] -0.132434074 -0.053461478 -0.688639329 1.158164820 -0.165614987
[66] 0.684235936 0.963916198 0.080934222 -1.917224233 0.169103207
[71] 0.614616939 -0.764055606 0.338875560 0.674894288 -0.453986289
[76] 1.344686048 0.184668835 0.160990076 0.886968377 0.894569878
[81] 1.967833071 -0.037127776 0.769285682 -0.047593035 1.227662027
[86] -1.943373558 -1.878047774 1.144127246 -2.061389693 -0.165995722
[91] -0.066177267 0.558382547 0.983762822 -0.407458057 -1.072898589
[96] -1.530047323 0.529293162 0.968183269 -0.973429566 -0.092059366
> colSums(tmp)
[1] 0.516197123 0.611815049 -0.436061869 0.427490743 -1.159860654
[6] -1.578263034 -0.676145828 -0.254589536 -1.660160081 -0.699024733
[11] 0.112533507 0.427416303 -1.476449748 0.397234819 0.579652865
[16] -0.902140030 -0.004798942 -0.217807557 -0.454352721 0.689827025
[21] -1.529578649 0.489081862 0.078172342 0.178261007 -1.425520547
[26] 0.738468238 0.090104159 1.384170151 0.619310303 0.469156450
[31] 0.352380763 -0.734349480 2.235438276 0.344000288 1.115510253
[36] 1.091180037 0.949792286 -0.809301412 0.865388338 -0.268247338
[41] -0.188950949 -1.453456521 0.687822081 0.800685710 -0.469372967
[46] -0.722152436 -2.113239942 1.094459352 -1.312417668 0.452734588
[51] -0.373167462 1.396168523 1.391953754 0.060037255 -0.611852752
[56] 1.134564407 -0.889555180 0.195563790 -1.096946815 -0.330332268
[61] -0.132434074 -0.053461478 -0.688639329 1.158164820 -0.165614987
[66] 0.684235936 0.963916198 0.080934222 -1.917224233 0.169103207
[71] 0.614616939 -0.764055606 0.338875560 0.674894288 -0.453986289
[76] 1.344686048 0.184668835 0.160990076 0.886968377 0.894569878
[81] 1.967833071 -0.037127776 0.769285682 -0.047593035 1.227662027
[86] -1.943373558 -1.878047774 1.144127246 -2.061389693 -0.165995722
[91] -0.066177267 0.558382547 0.983762822 -0.407458057 -1.072898589
[96] -1.530047323 0.529293162 0.968183269 -0.973429566 -0.092059366
> 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] 0.516197123 0.611815049 -0.436061869 0.427490743 -1.159860654
[6] -1.578263034 -0.676145828 -0.254589536 -1.660160081 -0.699024733
[11] 0.112533507 0.427416303 -1.476449748 0.397234819 0.579652865
[16] -0.902140030 -0.004798942 -0.217807557 -0.454352721 0.689827025
[21] -1.529578649 0.489081862 0.078172342 0.178261007 -1.425520547
[26] 0.738468238 0.090104159 1.384170151 0.619310303 0.469156450
[31] 0.352380763 -0.734349480 2.235438276 0.344000288 1.115510253
[36] 1.091180037 0.949792286 -0.809301412 0.865388338 -0.268247338
[41] -0.188950949 -1.453456521 0.687822081 0.800685710 -0.469372967
[46] -0.722152436 -2.113239942 1.094459352 -1.312417668 0.452734588
[51] -0.373167462 1.396168523 1.391953754 0.060037255 -0.611852752
[56] 1.134564407 -0.889555180 0.195563790 -1.096946815 -0.330332268
[61] -0.132434074 -0.053461478 -0.688639329 1.158164820 -0.165614987
[66] 0.684235936 0.963916198 0.080934222 -1.917224233 0.169103207
[71] 0.614616939 -0.764055606 0.338875560 0.674894288 -0.453986289
[76] 1.344686048 0.184668835 0.160990076 0.886968377 0.894569878
[81] 1.967833071 -0.037127776 0.769285682 -0.047593035 1.227662027
[86] -1.943373558 -1.878047774 1.144127246 -2.061389693 -0.165995722
[91] -0.066177267 0.558382547 0.983762822 -0.407458057 -1.072898589
[96] -1.530047323 0.529293162 0.968183269 -0.973429566 -0.092059366
> colMin(tmp)
[1] 0.516197123 0.611815049 -0.436061869 0.427490743 -1.159860654
[6] -1.578263034 -0.676145828 -0.254589536 -1.660160081 -0.699024733
[11] 0.112533507 0.427416303 -1.476449748 0.397234819 0.579652865
[16] -0.902140030 -0.004798942 -0.217807557 -0.454352721 0.689827025
[21] -1.529578649 0.489081862 0.078172342 0.178261007 -1.425520547
[26] 0.738468238 0.090104159 1.384170151 0.619310303 0.469156450
[31] 0.352380763 -0.734349480 2.235438276 0.344000288 1.115510253
[36] 1.091180037 0.949792286 -0.809301412 0.865388338 -0.268247338
[41] -0.188950949 -1.453456521 0.687822081 0.800685710 -0.469372967
[46] -0.722152436 -2.113239942 1.094459352 -1.312417668 0.452734588
[51] -0.373167462 1.396168523 1.391953754 0.060037255 -0.611852752
[56] 1.134564407 -0.889555180 0.195563790 -1.096946815 -0.330332268
[61] -0.132434074 -0.053461478 -0.688639329 1.158164820 -0.165614987
[66] 0.684235936 0.963916198 0.080934222 -1.917224233 0.169103207
[71] 0.614616939 -0.764055606 0.338875560 0.674894288 -0.453986289
[76] 1.344686048 0.184668835 0.160990076 0.886968377 0.894569878
[81] 1.967833071 -0.037127776 0.769285682 -0.047593035 1.227662027
[86] -1.943373558 -1.878047774 1.144127246 -2.061389693 -0.165995722
[91] -0.066177267 0.558382547 0.983762822 -0.407458057 -1.072898589
[96] -1.530047323 0.529293162 0.968183269 -0.973429566 -0.092059366
> colMedians(tmp)
[1] 0.516197123 0.611815049 -0.436061869 0.427490743 -1.159860654
[6] -1.578263034 -0.676145828 -0.254589536 -1.660160081 -0.699024733
[11] 0.112533507 0.427416303 -1.476449748 0.397234819 0.579652865
[16] -0.902140030 -0.004798942 -0.217807557 -0.454352721 0.689827025
[21] -1.529578649 0.489081862 0.078172342 0.178261007 -1.425520547
[26] 0.738468238 0.090104159 1.384170151 0.619310303 0.469156450
[31] 0.352380763 -0.734349480 2.235438276 0.344000288 1.115510253
[36] 1.091180037 0.949792286 -0.809301412 0.865388338 -0.268247338
[41] -0.188950949 -1.453456521 0.687822081 0.800685710 -0.469372967
[46] -0.722152436 -2.113239942 1.094459352 -1.312417668 0.452734588
[51] -0.373167462 1.396168523 1.391953754 0.060037255 -0.611852752
[56] 1.134564407 -0.889555180 0.195563790 -1.096946815 -0.330332268
[61] -0.132434074 -0.053461478 -0.688639329 1.158164820 -0.165614987
[66] 0.684235936 0.963916198 0.080934222 -1.917224233 0.169103207
[71] 0.614616939 -0.764055606 0.338875560 0.674894288 -0.453986289
[76] 1.344686048 0.184668835 0.160990076 0.886968377 0.894569878
[81] 1.967833071 -0.037127776 0.769285682 -0.047593035 1.227662027
[86] -1.943373558 -1.878047774 1.144127246 -2.061389693 -0.165995722
[91] -0.066177267 0.558382547 0.983762822 -0.407458057 -1.072898589
[96] -1.530047323 0.529293162 0.968183269 -0.973429566 -0.092059366
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.5161971 0.611815 -0.4360619 0.4274907 -1.159861 -1.578263 -0.6761458
[2,] 0.5161971 0.611815 -0.4360619 0.4274907 -1.159861 -1.578263 -0.6761458
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.2545895 -1.66016 -0.6990247 0.1125335 0.4274163 -1.47645 0.3972348
[2,] -0.2545895 -1.66016 -0.6990247 0.1125335 0.4274163 -1.47645 0.3972348
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 0.5796529 -0.90214 -0.004798942 -0.2178076 -0.4543527 0.689827 -1.529579
[2,] 0.5796529 -0.90214 -0.004798942 -0.2178076 -0.4543527 0.689827 -1.529579
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 0.4890819 0.07817234 0.178261 -1.425521 0.7384682 0.09010416 1.38417
[2,] 0.4890819 0.07817234 0.178261 -1.425521 0.7384682 0.09010416 1.38417
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 0.6193103 0.4691564 0.3523808 -0.7343495 2.235438 0.3440003 1.11551
[2,] 0.6193103 0.4691564 0.3523808 -0.7343495 2.235438 0.3440003 1.11551
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 1.09118 0.9497923 -0.8093014 0.8653883 -0.2682473 -0.1889509 -1.453457
[2,] 1.09118 0.9497923 -0.8093014 0.8653883 -0.2682473 -0.1889509 -1.453457
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 0.6878221 0.8006857 -0.469373 -0.7221524 -2.11324 1.094459 -1.312418
[2,] 0.6878221 0.8006857 -0.469373 -0.7221524 -2.11324 1.094459 -1.312418
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 0.4527346 -0.3731675 1.396169 1.391954 0.06003726 -0.6118528 1.134564
[2,] 0.4527346 -0.3731675 1.396169 1.391954 0.06003726 -0.6118528 1.134564
[,57] [,58] [,59] [,60] [,61] [,62]
[1,] -0.8895552 0.1955638 -1.096947 -0.3303323 -0.1324341 -0.05346148
[2,] -0.8895552 0.1955638 -1.096947 -0.3303323 -0.1324341 -0.05346148
[,63] [,64] [,65] [,66] [,67] [,68] [,69]
[1,] -0.6886393 1.158165 -0.165615 0.6842359 0.9639162 0.08093422 -1.917224
[2,] -0.6886393 1.158165 -0.165615 0.6842359 0.9639162 0.08093422 -1.917224
[,70] [,71] [,72] [,73] [,74] [,75] [,76]
[1,] 0.1691032 0.6146169 -0.7640556 0.3388756 0.6748943 -0.4539863 1.344686
[2,] 0.1691032 0.6146169 -0.7640556 0.3388756 0.6748943 -0.4539863 1.344686
[,77] [,78] [,79] [,80] [,81] [,82] [,83]
[1,] 0.1846688 0.1609901 0.8869684 0.8945699 1.967833 -0.03712778 0.7692857
[2,] 0.1846688 0.1609901 0.8869684 0.8945699 1.967833 -0.03712778 0.7692857
[,84] [,85] [,86] [,87] [,88] [,89] [,90]
[1,] -0.04759304 1.227662 -1.943374 -1.878048 1.144127 -2.06139 -0.1659957
[2,] -0.04759304 1.227662 -1.943374 -1.878048 1.144127 -2.06139 -0.1659957
[,91] [,92] [,93] [,94] [,95] [,96] [,97]
[1,] -0.06617727 0.5583825 0.9837628 -0.4074581 -1.072899 -1.530047 0.5292932
[2,] -0.06617727 0.5583825 0.9837628 -0.4074581 -1.072899 -1.530047 0.5292932
[,98] [,99] [,100]
[1,] 0.9681833 -0.9734296 -0.09205937
[2,] 0.9681833 -0.9734296 -0.09205937
>
>
> Max(tmp2)
[1] 2.316377
> Min(tmp2)
[1] -2.36343
> mean(tmp2)
[1] 0.01291475
> Sum(tmp2)
[1] 1.291475
> Var(tmp2)
[1] 0.9674074
>
> rowMeans(tmp2)
[1] -1.348305346 -0.244028980 -0.581872589 -1.256818401 0.290618485
[6] 1.184164969 -1.595461769 -1.304871069 0.284968256 0.056980046
[11] -0.295646853 0.011234306 -0.848929857 0.027093655 1.330555911
[16] 1.018250061 1.316681813 0.475678215 -0.789614870 0.145589249
[21] -0.363970051 -0.677197443 -1.469134877 1.288299435 2.057353433
[26] 1.392729036 0.689989581 -0.004503883 -1.159204474 -1.082645341
[31] -1.071473172 -0.351333131 -1.692140687 1.171945020 0.970425179
[36] 0.924621548 1.572782544 1.074154964 0.602397866 0.308947841
[41] -0.991656840 -2.093523867 0.722685324 0.828665712 -1.549169444
[46] -0.091636935 0.022930634 -0.466923359 1.030523446 -1.345432237
[51] -1.039058257 0.059004718 -0.277877186 0.250490421 0.830457795
[56] -1.154923325 0.740316730 -1.664770494 1.210511281 -0.293875956
[61] -0.935698358 0.860150548 0.376548544 -0.864311772 -0.671631817
[66] 1.840194612 -1.570672534 1.426774628 -0.181765172 0.818462842
[71] -0.134577097 -0.424076820 1.120213855 -0.152674067 -0.184014396
[76] 1.501032928 0.466473420 0.384179411 2.316377353 1.056381944
[81] -0.420176380 0.162663736 0.336953503 -0.309668083 -0.161637403
[86] -2.363430321 0.012263136 -0.044983632 1.099672251 1.115685979
[91] -0.341077640 -0.877240056 1.338826163 -0.016804571 -0.062033849
[96] -0.253753232 -0.541273814 -0.521756965 -0.897945540 0.204776710
> rowSums(tmp2)
[1] -1.348305346 -0.244028980 -0.581872589 -1.256818401 0.290618485
[6] 1.184164969 -1.595461769 -1.304871069 0.284968256 0.056980046
[11] -0.295646853 0.011234306 -0.848929857 0.027093655 1.330555911
[16] 1.018250061 1.316681813 0.475678215 -0.789614870 0.145589249
[21] -0.363970051 -0.677197443 -1.469134877 1.288299435 2.057353433
[26] 1.392729036 0.689989581 -0.004503883 -1.159204474 -1.082645341
[31] -1.071473172 -0.351333131 -1.692140687 1.171945020 0.970425179
[36] 0.924621548 1.572782544 1.074154964 0.602397866 0.308947841
[41] -0.991656840 -2.093523867 0.722685324 0.828665712 -1.549169444
[46] -0.091636935 0.022930634 -0.466923359 1.030523446 -1.345432237
[51] -1.039058257 0.059004718 -0.277877186 0.250490421 0.830457795
[56] -1.154923325 0.740316730 -1.664770494 1.210511281 -0.293875956
[61] -0.935698358 0.860150548 0.376548544 -0.864311772 -0.671631817
[66] 1.840194612 -1.570672534 1.426774628 -0.181765172 0.818462842
[71] -0.134577097 -0.424076820 1.120213855 -0.152674067 -0.184014396
[76] 1.501032928 0.466473420 0.384179411 2.316377353 1.056381944
[81] -0.420176380 0.162663736 0.336953503 -0.309668083 -0.161637403
[86] -2.363430321 0.012263136 -0.044983632 1.099672251 1.115685979
[91] -0.341077640 -0.877240056 1.338826163 -0.016804571 -0.062033849
[96] -0.253753232 -0.541273814 -0.521756965 -0.897945540 0.204776710
> rowVars(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowSd(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowMax(tmp2)
[1] -1.348305346 -0.244028980 -0.581872589 -1.256818401 0.290618485
[6] 1.184164969 -1.595461769 -1.304871069 0.284968256 0.056980046
[11] -0.295646853 0.011234306 -0.848929857 0.027093655 1.330555911
[16] 1.018250061 1.316681813 0.475678215 -0.789614870 0.145589249
[21] -0.363970051 -0.677197443 -1.469134877 1.288299435 2.057353433
[26] 1.392729036 0.689989581 -0.004503883 -1.159204474 -1.082645341
[31] -1.071473172 -0.351333131 -1.692140687 1.171945020 0.970425179
[36] 0.924621548 1.572782544 1.074154964 0.602397866 0.308947841
[41] -0.991656840 -2.093523867 0.722685324 0.828665712 -1.549169444
[46] -0.091636935 0.022930634 -0.466923359 1.030523446 -1.345432237
[51] -1.039058257 0.059004718 -0.277877186 0.250490421 0.830457795
[56] -1.154923325 0.740316730 -1.664770494 1.210511281 -0.293875956
[61] -0.935698358 0.860150548 0.376548544 -0.864311772 -0.671631817
[66] 1.840194612 -1.570672534 1.426774628 -0.181765172 0.818462842
[71] -0.134577097 -0.424076820 1.120213855 -0.152674067 -0.184014396
[76] 1.501032928 0.466473420 0.384179411 2.316377353 1.056381944
[81] -0.420176380 0.162663736 0.336953503 -0.309668083 -0.161637403
[86] -2.363430321 0.012263136 -0.044983632 1.099672251 1.115685979
[91] -0.341077640 -0.877240056 1.338826163 -0.016804571 -0.062033849
[96] -0.253753232 -0.541273814 -0.521756965 -0.897945540 0.204776710
> rowMin(tmp2)
[1] -1.348305346 -0.244028980 -0.581872589 -1.256818401 0.290618485
[6] 1.184164969 -1.595461769 -1.304871069 0.284968256 0.056980046
[11] -0.295646853 0.011234306 -0.848929857 0.027093655 1.330555911
[16] 1.018250061 1.316681813 0.475678215 -0.789614870 0.145589249
[21] -0.363970051 -0.677197443 -1.469134877 1.288299435 2.057353433
[26] 1.392729036 0.689989581 -0.004503883 -1.159204474 -1.082645341
[31] -1.071473172 -0.351333131 -1.692140687 1.171945020 0.970425179
[36] 0.924621548 1.572782544 1.074154964 0.602397866 0.308947841
[41] -0.991656840 -2.093523867 0.722685324 0.828665712 -1.549169444
[46] -0.091636935 0.022930634 -0.466923359 1.030523446 -1.345432237
[51] -1.039058257 0.059004718 -0.277877186 0.250490421 0.830457795
[56] -1.154923325 0.740316730 -1.664770494 1.210511281 -0.293875956
[61] -0.935698358 0.860150548 0.376548544 -0.864311772 -0.671631817
[66] 1.840194612 -1.570672534 1.426774628 -0.181765172 0.818462842
[71] -0.134577097 -0.424076820 1.120213855 -0.152674067 -0.184014396
[76] 1.501032928 0.466473420 0.384179411 2.316377353 1.056381944
[81] -0.420176380 0.162663736 0.336953503 -0.309668083 -0.161637403
[86] -2.363430321 0.012263136 -0.044983632 1.099672251 1.115685979
[91] -0.341077640 -0.877240056 1.338826163 -0.016804571 -0.062033849
[96] -0.253753232 -0.541273814 -0.521756965 -0.897945540 0.204776710
>
> colMeans(tmp2)
[1] 0.01291475
> colSums(tmp2)
[1] 1.291475
> colVars(tmp2)
[1] 0.9674074
> colSd(tmp2)
[1] 0.9835687
> colMax(tmp2)
[1] 2.316377
> colMin(tmp2)
[1] -2.36343
> colMedians(tmp2)
[1] -0.01065423
> colRanges(tmp2)
[,1]
[1,] -2.363430
[2,] 2.316377
>
> 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] -0.2170796 -4.9986254 0.5381088 6.2057227 4.3081117 -6.3456258
[7] -0.5266339 3.7045224 -1.8135733 5.7686725
> colApply(tmp,quantile)[,1]
[,1]
[1,] -2.5863175
[2,] -0.4411161
[3,] -0.1047584
[4,] 0.6298764
[5,] 1.5658475
>
> rowApply(tmp,sum)
[1] -3.65760307 0.90597467 5.93018163 0.29096257 -0.57644249 0.95863288
[7] 1.44060074 2.64844532 -1.23882901 -0.07832325
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 9 6 2 10 6 6 4 9 4 1
[2,] 1 1 7 1 4 3 1 8 6 6
[3,] 2 8 4 5 1 4 9 5 2 10
[4,] 8 5 5 8 9 9 10 6 9 4
[5,] 10 10 6 4 10 2 7 1 8 5
[6,] 3 3 9 6 3 1 5 3 1 7
[7,] 6 4 3 3 8 8 2 4 5 3
[8,] 5 2 10 9 2 10 8 7 3 8
[9,] 4 9 8 2 5 7 6 2 7 2
[10,] 7 7 1 7 7 5 3 10 10 9
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 4.2056823 0.2949771 -1.2697793 -2.3160855 1.5378611 2.4058693
[7] 0.6960063 -2.6802074 0.5490879 -0.9059771 -3.9120436 -2.4048042
[13] 0.3953194 4.2138239 1.3765591 1.2939285 -2.0022194 1.6820885
[19] -0.4658175 0.9395937
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.8907970
[2,] -0.1290778
[3,] 0.1770352
[4,] 2.4555849
[5,] 2.5929370
>
> rowApply(tmp,sum)
[1] -7.0107830 0.9000060 2.8396959 7.0593839 -0.1544398
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 10 20 11 20 5
[2,] 13 13 7 10 7
[3,] 11 17 2 3 9
[4,] 5 3 4 16 6
[5,] 20 8 18 1 18
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -0.1290778 -0.04164082 -0.09551428 -1.0370428 1.3131976 -0.2122349
[2,] 2.5929370 0.69007150 1.02086451 -1.0726390 -0.6212069 0.8001467
[3,] 0.1770352 -0.37642338 -0.97558056 -0.8844186 1.7359316 1.7587242
[4,] 2.4555849 0.46392000 -0.86841796 1.3049233 -1.9734550 0.4674129
[5,] -0.8907970 -0.44095023 -0.35113098 -0.6269084 1.0833938 -0.4081797
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -0.511035441 -1.2292320 -2.2887002 -0.6399892 -1.5344306 -0.0384765
[2,] -0.403014461 0.3114099 -0.8078514 -0.2657790 -0.8536494 -0.9795258
[3,] 0.005347497 -0.8684073 1.8841940 0.1614003 -0.3831281 0.3937524
[4,] 1.067863086 -0.8024971 0.5959343 -0.6146564 0.4362627 -0.7182240
[5,] 0.536845579 -0.0914808 1.1655111 0.4530471 -1.5770983 -1.0623303
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.6763589 0.4493087 0.2038325 -0.09263745 0.7282193 -2.2683600
[2,] 0.7744038 1.8282035 -2.2513509 1.37280652 -1.6462750 0.8835107
[3,] 0.6887933 0.3107604 0.9181609 0.21605070 -0.9075145 0.3701172
[4,] -1.0591551 1.3322180 1.7734352 -0.86150319 1.1093875 1.0776252
[5,] 0.6676362 0.2933334 0.7324813 0.65921194 -1.2860367 1.6191954
[,19] [,20]
[1,] 0.2018116 0.8875781
[2,] -0.8215902 0.3485338
[3,] -1.1541123 -0.2309871
[4,] 2.2238554 -0.3511297
[5,] -0.9157819 0.2855987
>
>
> 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 : 653 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 : 565 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 1.27475 1.49458 0.6975369 0.7156052 1.327338 -0.7978994 0.2335818
col8 col9 col10 col11 col12 col13 col14
row1 -0.1736923 -0.059203 0.09967723 -1.065725 0.4923768 0.09066884 -0.629106
col15 col16 col17 col18 col19 col20
row1 0.9289086 0.3109203 0.048317 -1.143472 0.6382645 0.3714423
> tmp[,"col10"]
col10
row1 0.09967723
row2 0.93117470
row3 1.49274081
row4 -0.51809181
row5 1.05038283
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 1.274750 1.49458 0.6975369 0.7156052 1.32733848 -0.7978994 0.23358180
row5 1.349772 -2.68529 0.5412871 0.4498792 0.06322296 0.5181038 0.08738826
col8 col9 col10 col11 col12 col13
row1 -0.1736923 -0.059203 0.09967723 -1.0657246 0.49237679 0.09066884
row5 -1.0037992 -1.215814 1.05038283 0.6607725 -0.02777397 0.95028862
col14 col15 col16 col17 col18 col19 col20
row1 -0.629106 0.9289086 0.3109203 0.048317 -1.1434719 0.6382645 0.3714423
row5 -1.012299 -0.6260773 -1.1462892 -1.260900 -0.8379501 -0.3850652 -1.0920756
> tmp[,c("col6","col20")]
col6 col20
row1 -0.7978994 0.37144226
row2 -0.8968021 -1.08727915
row3 1.2237227 -0.01115002
row4 2.0315443 -0.35155086
row5 0.5181038 -1.09207561
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.7978994 0.3714423
row5 0.5181038 -1.0920756
>
>
>
>
> 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 52.09907 49.36991 49.38873 49.47367 49.24205 105.3022 50.02841 50.10727
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.08636 50.93804 49.57116 51.40839 51.33436 49.67286 50.18503 48.57393
col17 col18 col19 col20
row1 49.41343 49.92163 50.701 105.7793
> tmp[,"col10"]
col10
row1 50.93804
row2 30.24543
row3 29.43608
row4 31.39836
row5 49.56191
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 52.09907 49.36991 49.38873 49.47367 49.24205 105.3022 50.02841 50.10727
row5 51.18305 50.91713 51.15926 50.18188 50.82321 103.9548 49.98129 48.49401
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.08636 50.93804 49.57116 51.40839 51.33436 49.67286 50.18503 48.57393
row5 50.14776 49.56191 48.79536 49.91973 49.30190 49.52922 50.87328 48.49633
col17 col18 col19 col20
row1 49.41343 49.92163 50.70100 105.7793
row5 50.22109 48.88623 48.33776 104.7068
> tmp[,c("col6","col20")]
col6 col20
row1 105.30224 105.77931
row2 73.29761 75.94293
row3 74.03513 73.38675
row4 73.97368 77.29313
row5 103.95478 104.70682
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.3022 105.7793
row5 103.9548 104.7068
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.3022 105.7793
row5 103.9548 104.7068
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -0.34164259
[2,] -1.06014163
[3,] 0.96923749
[4,] 1.84459177
[5,] 0.00056615
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.20754806 -0.7920588
[2,] -0.64948980 0.3066525
[3,] -0.02509576 0.2638955
[4,] 0.19955144 1.6094266
[5,] -0.34982062 0.4220036
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 1.3693647 -0.1016813
[2,] -0.6787722 2.2668123
[3,] 0.4062143 0.7334119
[4,] 0.3278346 -1.0548806
[5,] -1.0962370 1.1747957
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 1.369365
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 1.3693647
[2,] -0.6787722
>
>
>
> 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 0.3606390 0.1520723 0.9033750 1.339499 1.5475829 -0.6315780 2.005671
row1 0.4911255 -0.8635034 0.0260379 -1.319728 0.5286998 -0.2089202 -1.194677
[,8] [,9] [,10] [,11] [,12] [,13]
row3 -0.1890101 3.1132339 -0.1628107 -0.01025498 -0.6329065 0.03905179
row1 -1.3552072 0.6853279 0.7864873 0.99994829 -1.6410615 -0.03959029
[,14] [,15] [,16] [,17] [,18] [,19]
row3 -0.6650896 0.3766145 -0.6704937 -0.8980431 0.07581054 -0.8524864
row1 -0.2348236 -0.4396162 0.1800778 -0.2250770 0.01852766 0.3782754
[,20]
row3 0.1283266
row1 -1.0433960
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.3460041 0.1133568 -0.06375017 -0.255326 -2.331769 -0.2840361 0.87589
[,8] [,9] [,10]
row2 1.56003 -0.3976945 -1.671806
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -1.612663 0.4888706 0.08432011 -0.05371445 2.115279 -1.905184 -0.1410343
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.6144736 -0.3151911 -0.7051251 0.1899458 -0.9427781 -1.154691 2.466355
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.6122908 -0.3677727 -0.2182564 0.3436341 -0.3401508 1.732861
>
>
> 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: 0x6000024f8420>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM13d6c730b1482"
[2] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM13d6c5c6f9dcf"
[3] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM13d6c23e1b072"
[4] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM13d6c36071ec5"
[5] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM13d6cd753339"
[6] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM13d6c975ea16"
[7] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM13d6c1c5b4f34"
[8] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM13d6c2eaced77"
[9] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM13d6c5b1a3791"
[10] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM13d6c16363f51"
[11] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM13d6c4376ea3b"
[12] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM13d6c340bea17"
[13] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM13d6c7a35a6b2"
[14] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM13d6c58532ecc"
[15] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM13d6c3d258061"
>
>
> ### 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: 0x6000024f4840>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x6000024f4840>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x6000024f4840>
> rowMedians(tmp)
[1] -0.587217356 -0.118085965 0.372753170 -0.043942473 -0.046760710
[6] 0.415036861 0.336259688 -0.338558931 -0.354087917 0.470134120
[11] 0.131086803 -0.105659958 0.460679044 0.476112233 0.450081804
[16] -0.234213692 -0.022571818 0.805685176 -0.197004216 -0.216082330
[21] 0.208593347 -0.460287823 0.194511839 0.360321758 0.651824478
[26] 0.094243681 -0.111198425 -0.390883935 0.258224308 -0.536842239
[31] -0.312112729 -0.478883371 0.336042345 0.198330915 -0.071633307
[36] 0.184444094 0.089081902 0.465041923 -0.184190281 0.222508626
[41] -0.113168907 0.148521529 -0.147152564 0.372293942 -0.224106346
[46] 0.036455914 0.051027767 0.241753334 -0.348067171 0.356589854
[51] 0.266286525 0.174582962 -0.370940211 -0.408865927 -0.481467966
[56] 0.208128530 0.261188912 0.605621234 0.128329209 0.006545635
[61] 0.138613816 -0.154249106 0.103964524 -0.068037615 -0.515995735
[66] -0.384749874 0.186154272 0.181308039 0.020526807 -0.044161787
[71] -0.553713542 0.455054630 -0.294551930 -0.336142950 -0.206005812
[76] -0.403228092 0.228320724 0.063969795 -0.305331125 -0.173651141
[81] -0.206851742 0.062851879 -0.066698086 0.106407021 0.402011680
[86] 0.194229017 0.540361204 -0.244107167 -0.317202155 0.044116785
[91] 0.816898142 0.015151539 -0.195163891 -0.136960625 0.034394361
[96] 0.127619283 0.302616777 0.266917169 -0.429906403 -0.256764405
[101] 0.375595671 0.296305772 -0.227519795 -0.382617978 -0.035433781
[106] 0.046817952 -0.167621165 0.346172975 0.138698515 0.049116250
[111] -0.169570865 -0.341657203 -0.253098209 0.006983665 -0.164112397
[116] -0.721182395 -0.147905885 -0.124353064 0.237441030 -0.264564223
[121] 0.009133390 -0.022066826 -0.137625520 0.140550054 0.182456955
[126] 0.040905406 0.244277465 0.002045225 -0.484013871 0.179093197
[131] -0.110935252 -0.003317092 0.744977441 -0.692024595 -0.302844973
[136] -0.153102560 -0.134837960 -0.388140623 -0.106511299 0.060354955
[141] -0.072722549 0.325169208 0.076934505 -0.275418264 0.375970077
[146] 0.408833816 0.281705964 -0.224238253 -0.697304703 0.103569152
[151] 0.454609769 0.184631526 0.655985347 0.441553483 0.018026125
[156] -0.234020663 -0.145349523 0.003685552 -0.027889011 -0.340425371
[161] 0.181368783 0.077366031 0.117517776 -0.406938756 -0.060176614
[166] 0.091660788 -0.047185624 0.277458314 0.112438631 0.277194427
[171] 0.205948385 0.177524261 0.373670581 -0.328341952 0.130887276
[176] -0.024296351 -0.461933126 -0.601175708 0.308155987 0.794693831
[181] 0.390645052 0.026837962 -0.252911027 0.285259031 0.554595484
[186] 0.017395500 0.210216617 0.087254721 -0.545024990 0.192991868
[191] 0.086759319 -0.656416018 -0.487653821 0.037833156 -0.248559743
[196] -0.186250521 0.626437513 0.135571909 0.048631825 -0.173886602
[201] 0.103584608 0.091316584 0.128598297 -0.564742764 -0.119657238
[206] -0.522569665 0.159066950 0.423884564 0.091475583 -0.051662250
[211] 0.497371433 -0.121195138 0.604102222 -0.343757210 -0.013355430
[216] 0.040125000 0.068628431 0.051689196 -0.202586600 -0.576201479
[221] 0.321998539 -0.440018906 -0.057997967 -0.066024084 0.018030855
[226] -0.743503824 0.645785079 -0.167266588 -0.109716623 0.182607142
>
> proc.time()
user system elapsed
0.630 3.179 3.974
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: 0x6000000b8000>
> .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: 0x6000000b8000>
> .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: 0x6000000b8000>
> .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: 0x6000000b8000>
> 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: 0x6000000b80c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000000b80c0>
> .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: 0x6000000b80c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000000b80c0>
> .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: 0x6000000b80c0>
> 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: 0x6000000b82a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000000b82a0>
> .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: 0x6000000b82a0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x6000000b82a0>
> .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: 0x6000000b82a0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x6000000b82a0>
> .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: 0x6000000b82a0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x6000000b82a0>
> .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: 0x6000000b82a0>
> 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: 0x6000000b8480>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x6000000b8480>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000000b8480>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000000b8480>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile141b02d40b112" "BufferedMatrixFile141b043f39708"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile141b02d40b112" "BufferedMatrixFile141b043f39708"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000000b8720>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000000b8720>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x6000000b8720>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x6000000b8720>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x6000000b8720>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x6000000b8720>
> .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: 0x6000000b8900>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000000b8900>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x6000000b8900>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x6000000b8900>
> 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: 0x6000000b8ae0>
> .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: 0x6000000b8ae0>
> rm(P)
>
> proc.time()
user system elapsed
0.107 0.035 0.138
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
0.110 0.022 0.128