Ben Bolstad
| Snapshot Date: 2025-10-23 14:17 -0400 (Thu, 23 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 2025-10-24 12:06 -0400 (Fri, 24 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" | 4898 |
| lconway | macOS 12.7.6 Monterey | x86_64 | 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root" | 4688 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root" | 4634 |
| taishan | Linux (openEuler 24.03 LTS) | aarch64 | 4.5.0 (2025-04-11) -- "How About a Twenty-Six" | 4658 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
| Package 257/2359 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.73.0 (landing page) Ben Bolstad
| nebbiolo2 | Linux (Ubuntu 24.04.3 LTS) / x86_64 | OK | OK | OK | | ||||||||
| lconway | macOS 12.7.6 Monterey / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| kjohnson3 | macOS 13.7.7 Ventura / arm64 | OK | OK | WARNINGS | OK | | ||||||||
| taishan | Linux (openEuler 24.03 LTS) / aarch64 | OK | 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: 2025-10-23 18:51:27 -0400 (Thu, 23 Oct 2025) |
| EndedAt: 2025-10-23 18:51:44 -0400 (Thu, 23 Oct 2025) |
| EllapsedTime: 16.2 seconds |
| RetCode: 0 |
| Status: WARNINGS |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 1 |
##############################################################################
##############################################################################
###
### Running command:
###
### /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings BufferedMatrix_1.73.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.5.1 Patched (2025-09-10 r88807)
* using platform: aarch64-apple-darwin20
* R was compiled by
Apple clang version 16.0.0 (clang-1600.0.26.6)
GNU Fortran (GCC) 14.2.0
* running under: macOS Ventura 13.7.7
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.73.0’
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘BufferedMatrix’ can be installed ... WARNING
Found the following significant warnings:
doubleBufferedMatrix.c:1580:7: warning: logical not is only applied to the left hand side of this bitwise operator [-Wlogical-not-parentheses]
See ‘/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/00install.out’ for details.
* used C compiler: ‘Apple clang version 15.0.0 (clang-1500.1.0.2.5)’
* used SDK: ‘MacOSX11.3.1.sdk’
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) BufferedMatrix-class.Rd:209: Lost braces; missing escapes or markup?
209 | $x^{power}$ elementwise of the matrix
| ^
prepare_Rd: createBufferedMatrix.Rd:26: Dropping empty section \keyword
prepare_Rd: createBufferedMatrix.Rd:17-18: Dropping empty section \details
prepare_Rd: createBufferedMatrix.Rd:15-16: Dropping empty section \value
prepare_Rd: createBufferedMatrix.Rd:19-20: Dropping empty section \references
prepare_Rd: createBufferedMatrix.Rd:21-22: Dropping empty section \seealso
prepare_Rd: createBufferedMatrix.Rd:23-24: Dropping empty section \examples
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking line endings in C/C++/Fortran sources/headers ... OK
* checking compiled code ... NOTE
Note: information on .o files is not available
* checking sizes of PDF files under ‘inst/doc’ ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... NONE
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
Running ‘Rcodetesting.R’
Running ‘c_code_level_tests.R’
Running ‘objectTesting.R’
Running ‘rawCalltesting.R’
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE
Status: 1 WARNING, 2 NOTEs
See
‘/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/Library/Frameworks/R.framework/Versions/4.5-arm64/Resources/library’
* installing *source* package ‘BufferedMatrix’ ...
** this is package ‘BufferedMatrix’ version ‘1.73.0’
** using staged installation
** libs
using C compiler: ‘Apple clang version 15.0.0 (clang-1500.1.0.2.5)’
using SDK: ‘MacOSX11.3.1.sdk’
clang -arch arm64 -std=gnu2x -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/arm64/include -fPIC -falign-functions=64 -Wall -g -O2 -c RBufferedMatrix.c -o RBufferedMatrix.o
clang -arch arm64 -std=gnu2x -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/arm64/include -fPIC -falign-functions=64 -Wall -g -O2 -c doubleBufferedMatrix.c -o doubleBufferedMatrix.o
doubleBufferedMatrix.c:1580:7: warning: logical not is only applied to the left hand side of this bitwise operator [-Wlogical-not-parentheses]
if (!(Matrix->readonly) & setting){
^ ~
doubleBufferedMatrix.c:1580:7: note: add parentheses after the '!' to evaluate the bitwise operator first
if (!(Matrix->readonly) & setting){
^
( )
doubleBufferedMatrix.c:1580:7: note: add parentheses around left hand side expression to silence this warning
if (!(Matrix->readonly) & setting){
^
( )
doubleBufferedMatrix.c:3327:12: warning: unused function 'sort_double' [-Wunused-function]
static int sort_double(const double *a1,const double *a2){
^
2 warnings generated.
clang -arch arm64 -std=gnu2x -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/arm64/include -fPIC -falign-functions=64 -Wall -g -O2 -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
clang -arch arm64 -std=gnu2x -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/arm64/include -fPIC -falign-functions=64 -Wall -g -O2 -c init_package.c -o init_package.o
clang -arch arm64 -std=gnu2x -dynamiclib -Wl,-headerpad_max_install_names -undefined dynamic_lookup -L/Library/Frameworks/R.framework/Resources/lib -L/opt/R/arm64/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -F/Library/Frameworks/R.framework/.. -framework R
installing to /Library/Frameworks/R.framework/Versions/4.5-arm64/Resources/library/00LOCK-BufferedMatrix/00new/BufferedMatrix/libs
** R
** inst
** byte-compile and prepare package for lazy loading
Creating a new generic function for ‘rowMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘rowSums’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colSums’ in package ‘BufferedMatrix’
Creating a generic function for ‘ncol’ from package ‘base’ in package ‘BufferedMatrix’
Creating a generic function for ‘nrow’ from package ‘base’ in package ‘BufferedMatrix’
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** checking absolute paths in shared objects and dynamic libraries
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (BufferedMatrix)
BufferedMatrix.Rcheck/tests/c_code_level_tests.Rout
R version 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix", "BufferedMatrix", .libPaths());.C("dbm_c_tester",integer(1))
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1
Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000
1.000000 2.000000 3.000000 4.000000 5.000000
2.000000 3.000000 4.000000 5.000000 6.000000
3.000000 4.000000 5.000000 6.000000 7.000000
4.000000 5.000000 6.000000 7.000000 8.000000
Adding Additional Column
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
0.000000 1.000000 2.000000 3.000000 4.000000 0.000000
1.000000 2.000000 3.000000 4.000000 5.000000 0.000000
2.000000 3.000000 4.000000 5.000000 6.000000 0.000000
3.000000 4.000000 5.000000 6.000000 7.000000 0.000000
4.000000 5.000000 6.000000 7.000000 8.000000 0.000000
Reassigning values
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 3
Buffer Cols: 3
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Activating Row Buffer
In row mode: 1
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Squaring Last Column
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
5.000000 10.000000 15.000000 20.000000 25.000000 900.000000
Square rooting Last Row, then turing off Row Buffer
In row mode: 0
Checking on value that should be not be in column buffer2.236068
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
2.236068 3.162278 3.872983 4.472136 5.000000 30.000000
Single Indexing. Assign each value its square
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Resizing Buffers Smaller
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Activating Row Mode.
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
Activating ReadOnly Mode.
The results of assignment is: 0
Printing matrix reversed.
900.000000 625.000000 400.000000 225.000000 100.000000 25.000000
841.000000 576.000000 361.000000 196.000000 81.000000 16.000000
784.000000 529.000000 324.000000 169.000000 64.000000 9.000000
729.000000 484.000000 289.000000 144.000000 49.000000 -30.000000
676.000000 441.000000 256.000000 121.000000 -20.000000 -10.000000
[[1]]
[1] 0
>
> proc.time()
user system elapsed
0.105 0.031 0.131
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
>
> ### this is used to control how many repetitions in something below
> ### higher values result in more checks.
> nreps <-100 ##20000
>
>
> ## test creation and some simple assignments and subsetting operations
>
> ## first on single elements
> tmp <- createBufferedMatrix(1000,10)
>
> tmp[10,5]
[1] 0
> tmp[10,5] <- 10
> tmp[10,5]
[1] 10
> tmp[10,5] <- 12.445
> tmp[10,5]
[1] 12.445
>
>
>
> ## now testing accessing multiple elements
> tmp2 <- createBufferedMatrix(10,20)
>
>
> tmp2[3,1] <- 51.34
> tmp2[9,2] <- 9.87654
> tmp2[,1:2]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[,-(3:20)]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 51.34 0 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
> tmp2[-3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
[2,] 0 0 0 0 0 0 0
[3,] 0 0 0 0 0 0 0
[4,] 0 0 0 0 0 0 0
[5,] 0 0 0 0 0 0 0
[6,] 0 0 0 0 0 0 0
[7,] 0 0 0 0 0 0 0
[8,] 0 0 0 0 0 0 0
[9,] 0 0 0 0 0 0 0
> tmp2[2,1:3]
[,1] [,2] [,3]
[1,] 0 0 0
> tmp2[3:9,1:3]
[,1] [,2] [,3]
[1,] 51.34 0.00000 0
[2,] 0.00 0.00000 0
[3,] 0.00 0.00000 0
[4,] 0.00 0.00000 0
[5,] 0.00 0.00000 0
[6,] 0.00 0.00000 0
[7,] 0.00 9.87654 0
> tmp2[-4,-4]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 51.34 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0.00 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19]
[1,] 0 0 0 0 0 0
[2,] 0 0 0 0 0 0
[3,] 0 0 0 0 0 0
[4,] 0 0 0 0 0 0
[5,] 0 0 0 0 0 0
[6,] 0 0 0 0 0 0
[7,] 0 0 0 0 0 0
[8,] 0 0 0 0 0 0
[9,] 0 0 0 0 0 0
>
> ## now testing accessing/assigning multiple elements
> tmp3 <- createBufferedMatrix(10,10)
>
> for (i in 1:10){
+ for (j in 1:10){
+ tmp3[i,j] <- (j-1)*10 + i
+ }
+ }
>
> tmp3[2:4,2:4]
[,1] [,2] [,3]
[1,] 12 22 32
[2,] 13 23 33
[3,] 14 24 34
> tmp3[c(-10),c(2:4,2:4,10,1,2,1:10,10:1)]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 11 21 31 11 21 31 91 1 11 1 11 21 31
[2,] 12 22 32 12 22 32 92 2 12 2 12 22 32
[3,] 13 23 33 13 23 33 93 3 13 3 13 23 33
[4,] 14 24 34 14 24 34 94 4 14 4 14 24 34
[5,] 15 25 35 15 25 35 95 5 15 5 15 25 35
[6,] 16 26 36 16 26 36 96 6 16 6 16 26 36
[7,] 17 27 37 17 27 37 97 7 17 7 17 27 37
[8,] 18 28 38 18 28 38 98 8 18 8 18 28 38
[9,] 19 29 39 19 29 39 99 9 19 9 19 29 39
[,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25]
[1,] 41 51 61 71 81 91 91 81 71 61 51 41
[2,] 42 52 62 72 82 92 92 82 72 62 52 42
[3,] 43 53 63 73 83 93 93 83 73 63 53 43
[4,] 44 54 64 74 84 94 94 84 74 64 54 44
[5,] 45 55 65 75 85 95 95 85 75 65 55 45
[6,] 46 56 66 76 86 96 96 86 76 66 56 46
[7,] 47 57 67 77 87 97 97 87 77 67 57 47
[8,] 48 58 68 78 88 98 98 88 78 68 58 48
[9,] 49 59 69 79 89 99 99 89 79 69 59 49
[,26] [,27] [,28] [,29]
[1,] 31 21 11 1
[2,] 32 22 12 2
[3,] 33 23 13 3
[4,] 34 24 14 4
[5,] 35 25 15 5
[6,] 36 26 16 6
[7,] 37 27 17 7
[8,] 38 28 18 8
[9,] 39 29 19 9
> tmp3[-c(1:5),-c(6:10)]
[,1] [,2] [,3] [,4] [,5]
[1,] 6 16 26 36 46
[2,] 7 17 27 37 47
[3,] 8 18 28 38 48
[4,] 9 19 29 39 49
[5,] 10 20 30 40 50
>
> ## assignment of whole columns
> tmp3[,1] <- c(1:10*100.0)
> tmp3[,1:2] <- tmp3[,1:2]*100
> tmp3[,1:2] <- tmp3[,2:1]
> tmp3[,1:2]
[,1] [,2]
[1,] 1100 1e+04
[2,] 1200 2e+04
[3,] 1300 3e+04
[4,] 1400 4e+04
[5,] 1500 5e+04
[6,] 1600 6e+04
[7,] 1700 7e+04
[8,] 1800 8e+04
[9,] 1900 9e+04
[10,] 2000 1e+05
>
>
> tmp3[,-1] <- tmp3[,1:9]
> tmp3[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1100 1100 1e+04 21 31 41 51 61 71 81
[2,] 1200 1200 2e+04 22 32 42 52 62 72 82
[3,] 1300 1300 3e+04 23 33 43 53 63 73 83
[4,] 1400 1400 4e+04 24 34 44 54 64 74 84
[5,] 1500 1500 5e+04 25 35 45 55 65 75 85
[6,] 1600 1600 6e+04 26 36 46 56 66 76 86
[7,] 1700 1700 7e+04 27 37 47 57 67 77 87
[8,] 1800 1800 8e+04 28 38 48 58 68 78 88
[9,] 1900 1900 9e+04 29 39 49 59 69 79 89
[10,] 2000 2000 1e+05 30 40 50 60 70 80 90
>
> tmp3[,1:2] <- rep(1,10)
> tmp3[,1:2] <- rep(1,20)
> tmp3[,1:2] <- matrix(c(1:5),1,5)
>
> tmp3[,-c(1:8)] <- matrix(c(1:5),1,5)
>
> tmp3[1,] <- 1:10
> tmp3[1,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
> tmp3[-1,] <- c(1,2)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 2 1 2 1 2 1 2 1 2 1
[10,] 1 2 1 2 1 2 1 2 1 2
> tmp3[-c(1:8),] <- matrix(c(1:5),1,5)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 1 3 5 2 4 1 3 5 2 4
[10,] 2 4 1 3 5 2 4 1 3 5
>
>
> tmp3[1:2,1:2] <- 5555.04
> tmp3[-(1:2),1:2] <- 1234.56789
>
>
>
> ## testing accessors for the directory and prefix
> directory(tmp3)
[1] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests"
> prefix(tmp3)
[1] "BM"
>
> ## testing if we can remove these objects
> rm(tmp, tmp2, tmp3)
> gc()
used (Mb) gc trigger (Mb) limit (Mb) max used (Mb)
Ncells 480828 25.7 1056615 56.5 NA 634357 33.9
Vcells 891019 6.8 8388608 64.0 196608 2109489 16.1
>
>
>
>
> ##
> ## checking reads
> ##
>
> tmp2 <- createBufferedMatrix(10,20)
>
> test.sample <- rnorm(10*20)
>
> tmp2[1:10,1:20] <- test.sample
>
> test.matrix <- matrix(test.sample,10,20)
>
> ## testing reads
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Thu Oct 23 18:51:37 2025"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Thu Oct 23 18:51:37 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: 0x60000158c300>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Thu Oct 23 18:51:38 2025"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Thu Oct 23 18:51:38 2025"
>
> ColMode(tmp2)
<pointer: 0x60000158c300>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 100.4331675 -0.859936996 0.1533044 -0.35588134
[2,] 0.4426491 0.001012366 -0.8749394 -1.32428899
[3,] 0.1350844 0.503463435 0.8478170 0.03475678
[4,] -2.0179713 -0.437744277 1.2458291 0.05436770
> 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,] 100.4331675 0.859936996 0.1533044 0.35588134
[2,] 0.4426491 0.001012366 0.8749394 1.32428899
[3,] 0.1350844 0.503463435 0.8478170 0.03475678
[4,] 2.0179713 0.437744277 1.2458291 0.05436770
> 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,] 10.0216350 0.9273279 0.3915411 0.5965579
[2,] 0.6653188 0.0318177 0.9353819 1.1507776
[3,] 0.3675383 0.7095516 0.9207698 0.1864317
[4,] 1.4205532 0.6616225 1.1161671 0.2331688
>
> 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,] 225.64952 35.13322 29.06872 31.32146
[2,] 32.09584 25.31919 35.22876 37.83206
[3,] 28.81047 32.59898 35.05551 26.89907
[4,] 41.22350 32.05397 37.40750 27.38606
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x600001594000>
> exp(tmp5)
<pointer: 0x600001594000>
> log(tmp5,2)
<pointer: 0x600001594000>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 469.6599
> Min(tmp5)
[1] 52.69858
> mean(tmp5)
[1] 72.16949
> Sum(tmp5)
[1] 14433.9
> Var(tmp5)
[1] 875.7852
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 90.85264 69.37650 70.80842 70.37398 66.95128 69.59096 71.00474 68.28533
[9] 74.98388 69.46715
> rowSums(tmp5)
[1] 1817.053 1387.530 1416.168 1407.480 1339.026 1391.819 1420.095 1365.707
[9] 1499.678 1389.343
> rowVars(tmp5)
[1] 8062.74313 96.85756 78.11996 76.99130 64.30816 60.24944
[7] 88.44269 46.06618 65.38607 83.55149
> rowSd(tmp5)
[1] 89.792779 9.841624 8.838550 8.774469 8.019237 7.762052 9.404397
[8] 6.787207 8.086165 9.140651
> rowMax(tmp5)
[1] 469.65991 84.48228 86.34672 85.80132 85.46583 86.40150 87.42610
[8] 79.79553 90.68409 83.72501
> rowMin(tmp5)
[1] 56.67997 52.69858 55.98690 54.80295 55.22327 58.24800 55.29711 54.69704
[9] 59.89791 53.85484
>
> colMeans(tmp5)
[1] 112.06088 71.88533 67.87693 64.71458 66.55168 69.74169 73.74815
[8] 72.08220 75.89727 66.21800 70.43908 69.88815 67.20144 68.11174
[15] 68.02372 73.53212 72.44690 71.64281 72.91523 68.41186
> colSums(tmp5)
[1] 1120.6088 718.8533 678.7693 647.1458 665.5168 697.4169 737.4815
[8] 720.8220 758.9727 662.1800 704.3908 698.8815 672.0144 681.1174
[15] 680.2372 735.3212 724.4690 716.4281 729.1523 684.1186
> colVars(tmp5)
[1] 15853.55222 115.37931 58.11595 62.82298 60.89169 81.00140
[7] 82.38200 39.65357 49.45697 45.58299 85.75373 96.88855
[13] 54.91958 127.53070 95.49120 87.98596 73.49301 87.00089
[19] 98.00338 66.34880
> colSd(tmp5)
[1] 125.910890 10.741476 7.623382 7.926095 7.803313 9.000078
[7] 9.076453 6.297108 7.032565 6.751518 9.260331 9.843198
[13] 7.410775 11.292949 9.771960 9.380083 8.572806 9.327427
[19] 9.899666 8.145478
> colMax(tmp5)
[1] 469.65991 86.09142 77.85881 78.74249 83.08472 88.20661 86.51160
[8] 79.79553 86.34672 76.45585 84.48228 86.40150 77.56128 83.94014
[15] 80.05161 90.68409 83.72501 87.42610 85.19088 85.39259
> colMin(tmp5)
[1] 59.96521 52.69858 57.05606 55.98690 58.87973 60.12073 61.88024 56.99954
[9] 65.05507 58.24800 54.80295 53.85484 55.22327 54.69704 55.32171 56.65567
[17] 58.11060 61.19287 56.33710 60.09285
>
>
> ### setting a random element to NA and then testing with na.rm=TRUE or na.rm=FALSE (The default)
>
>
> which.row <- sample(1:10,1,replace=TRUE)
> which.col <- sample(1:20,1,replace=TRUE)
>
> tmp5[which.row,which.col] <- NA
>
> Max(tmp5)
[1] NA
> Min(tmp5)
[1] NA
> mean(tmp5)
[1] NA
> Sum(tmp5)
[1] NA
> Var(tmp5)
[1] NA
>
> rowMeans(tmp5)
[1] 90.85264 69.37650 70.80842 70.37398 66.95128 69.59096 NA 68.28533
[9] 74.98388 69.46715
> rowSums(tmp5)
[1] 1817.053 1387.530 1416.168 1407.480 1339.026 1391.819 NA 1365.707
[9] 1499.678 1389.343
> rowVars(tmp5)
[1] 8062.74313 96.85756 78.11996 76.99130 64.30816 60.24944
[7] 93.11499 46.06618 65.38607 83.55149
> rowSd(tmp5)
[1] 89.792779 9.841624 8.838550 8.774469 8.019237 7.762052 9.649611
[8] 6.787207 8.086165 9.140651
> rowMax(tmp5)
[1] 469.65991 84.48228 86.34672 85.80132 85.46583 86.40150 NA
[8] 79.79553 90.68409 83.72501
> rowMin(tmp5)
[1] 56.67997 52.69858 55.98690 54.80295 55.22327 58.24800 NA 54.69704
[9] 59.89791 53.85484
>
> colMeans(tmp5)
[1] 112.06088 71.88533 67.87693 64.71458 66.55168 69.74169 73.74815
[8] 72.08220 75.89727 66.21800 70.43908 69.88815 67.20144 68.11174
[15] NA 73.53212 72.44690 71.64281 72.91523 68.41186
> colSums(tmp5)
[1] 1120.6088 718.8533 678.7693 647.1458 665.5168 697.4169 737.4815
[8] 720.8220 758.9727 662.1800 704.3908 698.8815 672.0144 681.1174
[15] NA 735.3212 724.4690 716.4281 729.1523 684.1186
> colVars(tmp5)
[1] 15853.55222 115.37931 58.11595 62.82298 60.89169 81.00140
[7] 82.38200 39.65357 49.45697 45.58299 85.75373 96.88855
[13] 54.91958 127.53070 NA 87.98596 73.49301 87.00089
[19] 98.00338 66.34880
> colSd(tmp5)
[1] 125.910890 10.741476 7.623382 7.926095 7.803313 9.000078
[7] 9.076453 6.297108 7.032565 6.751518 9.260331 9.843198
[13] 7.410775 11.292949 NA 9.380083 8.572806 9.327427
[19] 9.899666 8.145478
> colMax(tmp5)
[1] 469.65991 86.09142 77.85881 78.74249 83.08472 88.20661 86.51160
[8] 79.79553 86.34672 76.45585 84.48228 86.40150 77.56128 83.94014
[15] NA 90.68409 83.72501 87.42610 85.19088 85.39259
> colMin(tmp5)
[1] 59.96521 52.69858 57.05606 55.98690 58.87973 60.12073 61.88024 56.99954
[9] 65.05507 58.24800 54.80295 53.85484 55.22327 54.69704 NA 56.65567
[17] 58.11060 61.19287 56.33710 60.09285
>
> Max(tmp5,na.rm=TRUE)
[1] 469.6599
> Min(tmp5,na.rm=TRUE)
[1] 52.69858
> mean(tmp5,na.rm=TRUE)
[1] 72.18555
> Sum(tmp5,na.rm=TRUE)
[1] 14364.92
> Var(tmp5,na.rm=TRUE)
[1] 880.1565
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.85264 69.37650 70.80842 70.37398 66.95128 69.59096 71.11163 68.28533
[9] 74.98388 69.46715
> rowSums(tmp5,na.rm=TRUE)
[1] 1817.053 1387.530 1416.168 1407.480 1339.026 1391.819 1351.121 1365.707
[9] 1499.678 1389.343
> rowVars(tmp5,na.rm=TRUE)
[1] 8062.74313 96.85756 78.11996 76.99130 64.30816 60.24944
[7] 93.11499 46.06618 65.38607 83.55149
> rowSd(tmp5,na.rm=TRUE)
[1] 89.792779 9.841624 8.838550 8.774469 8.019237 7.762052 9.649611
[8] 6.787207 8.086165 9.140651
> rowMax(tmp5,na.rm=TRUE)
[1] 469.65991 84.48228 86.34672 85.80132 85.46583 86.40150 87.42610
[8] 79.79553 90.68409 83.72501
> rowMin(tmp5,na.rm=TRUE)
[1] 56.67997 52.69858 55.98690 54.80295 55.22327 58.24800 55.29711 54.69704
[9] 59.89791 53.85484
>
> colMeans(tmp5,na.rm=TRUE)
[1] 112.06088 71.88533 67.87693 64.71458 66.55168 69.74169 73.74815
[8] 72.08220 75.89727 66.21800 70.43908 69.88815 67.20144 68.11174
[15] 67.91815 73.53212 72.44690 71.64281 72.91523 68.41186
> colSums(tmp5,na.rm=TRUE)
[1] 1120.6088 718.8533 678.7693 647.1458 665.5168 697.4169 737.4815
[8] 720.8220 758.9727 662.1800 704.3908 698.8815 672.0144 681.1174
[15] 611.2633 735.3212 724.4690 716.4281 729.1523 684.1186
> colVars(tmp5,na.rm=TRUE)
[1] 15853.55222 115.37931 58.11595 62.82298 60.89169 81.00140
[7] 82.38200 39.65357 49.45697 45.58299 85.75373 96.88855
[13] 54.91958 127.53070 107.30220 87.98596 73.49301 87.00089
[19] 98.00338 66.34880
> colSd(tmp5,na.rm=TRUE)
[1] 125.910890 10.741476 7.623382 7.926095 7.803313 9.000078
[7] 9.076453 6.297108 7.032565 6.751518 9.260331 9.843198
[13] 7.410775 11.292949 10.358678 9.380083 8.572806 9.327427
[19] 9.899666 8.145478
> colMax(tmp5,na.rm=TRUE)
[1] 469.65991 86.09142 77.85881 78.74249 83.08472 88.20661 86.51160
[8] 79.79553 86.34672 76.45585 84.48228 86.40150 77.56128 83.94014
[15] 80.05161 90.68409 83.72501 87.42610 85.19088 85.39259
> colMin(tmp5,na.rm=TRUE)
[1] 59.96521 52.69858 57.05606 55.98690 58.87973 60.12073 61.88024 56.99954
[9] 65.05507 58.24800 54.80295 53.85484 55.22327 54.69704 55.32171 56.65567
[17] 58.11060 61.19287 56.33710 60.09285
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.85264 69.37650 70.80842 70.37398 66.95128 69.59096 NaN 68.28533
[9] 74.98388 69.46715
> rowSums(tmp5,na.rm=TRUE)
[1] 1817.053 1387.530 1416.168 1407.480 1339.026 1391.819 0.000 1365.707
[9] 1499.678 1389.343
> rowVars(tmp5,na.rm=TRUE)
[1] 8062.74313 96.85756 78.11996 76.99130 64.30816 60.24944
[7] NA 46.06618 65.38607 83.55149
> rowSd(tmp5,na.rm=TRUE)
[1] 89.792779 9.841624 8.838550 8.774469 8.019237 7.762052 NA
[8] 6.787207 8.086165 9.140651
> rowMax(tmp5,na.rm=TRUE)
[1] 469.65991 84.48228 86.34672 85.80132 85.46583 86.40150 NA
[8] 79.79553 90.68409 83.72501
> rowMin(tmp5,na.rm=TRUE)
[1] 56.67997 52.69858 55.98690 54.80295 55.22327 58.24800 NA 54.69704
[9] 59.89791 53.85484
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 115.19145 70.30688 68.70746 63.82566 64.71467 69.39266 74.95316
[8] 72.24538 75.50026 65.83185 71.10722 70.13892 66.92320 69.53559
[15] NaN 73.11847 73.02731 69.88911 74.67427 68.97641
> colSums(tmp5,na.rm=TRUE)
[1] 1036.7231 632.7619 618.3672 574.4309 582.4321 624.5339 674.5784
[8] 650.2084 679.5023 592.4867 639.9650 631.2503 602.3088 625.8203
[15] 0.0000 658.0662 657.2458 629.0020 672.0684 620.7877
> colVars(tmp5,na.rm=TRUE)
[1] 17724.99113 101.77217 57.62028 61.78626 30.53906 89.75605
[7] 76.34411 44.31070 53.86589 49.60339 91.45077 108.29215
[13] 60.91360 120.66442 NA 97.05922 78.88972 63.27707
[19] 75.44387 71.05689
> colSd(tmp5,na.rm=TRUE)
[1] 133.135236 10.088219 7.590802 7.860424 5.526216 9.473967
[7] 8.737512 6.656628 7.339338 7.042968 9.562990 10.406351
[13] 7.804717 10.984736 NA 9.851864 8.881988 7.954688
[19] 8.685843 8.429525
> colMax(tmp5,na.rm=TRUE)
[1] 469.65991 85.46583 77.85881 78.74249 74.54885 88.20661 86.51160
[8] 79.79553 86.34672 76.45585 84.48228 86.40150 77.56128 83.94014
[15] -Inf 90.68409 83.72501 84.23339 85.19088 85.39259
> colMin(tmp5,na.rm=TRUE)
[1] 59.96521 52.69858 57.05606 55.98690 58.87973 60.12073 61.88024 56.99954
[9] 65.05507 58.24800 54.80295 53.85484 55.22327 54.69704 Inf 56.65567
[17] 58.11060 61.19287 56.33710 60.09285
>
>
>
>
> 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] 249.27663 285.01806 283.12333 177.05303 285.08128 215.16525 251.13747
[8] 236.68153 127.83303 78.49877
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 249.27663 285.01806 283.12333 177.05303 285.08128 215.16525 251.13747
[8] 236.68153 127.83303 78.49877
>
>
>
> 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] 8.526513e-14 -1.421085e-14 -1.136868e-13 2.842171e-14 -2.273737e-13
[6] -8.526513e-14 8.526513e-14 5.684342e-14 0.000000e+00 5.684342e-14
[11] 5.684342e-14 5.684342e-14 2.842171e-14 -2.842171e-14 -1.421085e-13
[16] 2.842171e-14 0.000000e+00 -9.947598e-14 1.136868e-13 0.000000e+00
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
9 17
9 18
7 1
9 20
4 3
6 1
10 6
8 18
10 17
5 11
8 12
4 17
1 18
4 8
9 7
1 1
8 19
8 13
2 4
9 6
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] 3.304967
> Min(tmp)
[1] -2.468855
> mean(tmp)
[1] -0.02506847
> Sum(tmp)
[1] -2.506847
> Var(tmp)
[1] 1.15116
>
> rowMeans(tmp)
[1] -0.02506847
> rowSums(tmp)
[1] -2.506847
> rowVars(tmp)
[1] 1.15116
> rowSd(tmp)
[1] 1.072921
> rowMax(tmp)
[1] 3.304967
> rowMin(tmp)
[1] -2.468855
>
> colMeans(tmp)
[1] -0.744403649 -0.933580925 -0.589925460 -0.574467203 -1.075860977
[6] -1.220145615 0.660435153 -0.744757181 0.137138128 -0.675909887
[11] 0.097653271 -1.287979171 -0.765995891 0.516109559 1.484669237
[16] -0.393475216 0.383462507 0.293164742 1.429658252 2.540223836
[21] -0.313305290 -0.469828846 0.219302992 0.466801024 0.125513438
[26] -0.839982743 0.214614851 0.007518155 0.806953023 0.587132039
[31] -1.676481837 0.999901847 1.305956609 0.131430106 -0.251904819
[36] 1.822088451 1.668619230 0.849101353 0.323234551 -1.077241876
[41] -1.782696246 -0.001262014 2.634765073 0.825036666 0.291661970
[46] 0.548204308 -0.139480178 0.320063466 -0.486473105 0.191993117
[51] 0.691638341 -0.662108615 0.330387900 -0.142410346 0.005868548
[56] -1.081719102 -1.245373266 -0.566688046 2.128663723 -1.314193365
[61] 0.120110543 1.111750667 0.834292854 1.939172780 -1.591232792
[66] 1.990882486 0.176456203 -0.286537559 0.208104236 0.534167829
[71] 0.145346556 -0.335194447 1.115444404 -0.978768086 -2.042583018
[76] -0.191708089 -1.333211777 0.146777437 -1.209961859 -0.847660747
[81] -2.468855346 0.359387166 3.304967337 -0.670903195 -0.918640559
[86] -0.392020248 -0.548465657 -0.100637510 1.218538248 0.688866969
[91] 1.579129124 -0.108180577 -0.958228275 -1.376456532 -1.704818068
[96] -0.742028196 -1.454774477 -0.490975555 -1.015602075 -0.194111548
> colSums(tmp)
[1] -0.744403649 -0.933580925 -0.589925460 -0.574467203 -1.075860977
[6] -1.220145615 0.660435153 -0.744757181 0.137138128 -0.675909887
[11] 0.097653271 -1.287979171 -0.765995891 0.516109559 1.484669237
[16] -0.393475216 0.383462507 0.293164742 1.429658252 2.540223836
[21] -0.313305290 -0.469828846 0.219302992 0.466801024 0.125513438
[26] -0.839982743 0.214614851 0.007518155 0.806953023 0.587132039
[31] -1.676481837 0.999901847 1.305956609 0.131430106 -0.251904819
[36] 1.822088451 1.668619230 0.849101353 0.323234551 -1.077241876
[41] -1.782696246 -0.001262014 2.634765073 0.825036666 0.291661970
[46] 0.548204308 -0.139480178 0.320063466 -0.486473105 0.191993117
[51] 0.691638341 -0.662108615 0.330387900 -0.142410346 0.005868548
[56] -1.081719102 -1.245373266 -0.566688046 2.128663723 -1.314193365
[61] 0.120110543 1.111750667 0.834292854 1.939172780 -1.591232792
[66] 1.990882486 0.176456203 -0.286537559 0.208104236 0.534167829
[71] 0.145346556 -0.335194447 1.115444404 -0.978768086 -2.042583018
[76] -0.191708089 -1.333211777 0.146777437 -1.209961859 -0.847660747
[81] -2.468855346 0.359387166 3.304967337 -0.670903195 -0.918640559
[86] -0.392020248 -0.548465657 -0.100637510 1.218538248 0.688866969
[91] 1.579129124 -0.108180577 -0.958228275 -1.376456532 -1.704818068
[96] -0.742028196 -1.454774477 -0.490975555 -1.015602075 -0.194111548
> 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] -0.744403649 -0.933580925 -0.589925460 -0.574467203 -1.075860977
[6] -1.220145615 0.660435153 -0.744757181 0.137138128 -0.675909887
[11] 0.097653271 -1.287979171 -0.765995891 0.516109559 1.484669237
[16] -0.393475216 0.383462507 0.293164742 1.429658252 2.540223836
[21] -0.313305290 -0.469828846 0.219302992 0.466801024 0.125513438
[26] -0.839982743 0.214614851 0.007518155 0.806953023 0.587132039
[31] -1.676481837 0.999901847 1.305956609 0.131430106 -0.251904819
[36] 1.822088451 1.668619230 0.849101353 0.323234551 -1.077241876
[41] -1.782696246 -0.001262014 2.634765073 0.825036666 0.291661970
[46] 0.548204308 -0.139480178 0.320063466 -0.486473105 0.191993117
[51] 0.691638341 -0.662108615 0.330387900 -0.142410346 0.005868548
[56] -1.081719102 -1.245373266 -0.566688046 2.128663723 -1.314193365
[61] 0.120110543 1.111750667 0.834292854 1.939172780 -1.591232792
[66] 1.990882486 0.176456203 -0.286537559 0.208104236 0.534167829
[71] 0.145346556 -0.335194447 1.115444404 -0.978768086 -2.042583018
[76] -0.191708089 -1.333211777 0.146777437 -1.209961859 -0.847660747
[81] -2.468855346 0.359387166 3.304967337 -0.670903195 -0.918640559
[86] -0.392020248 -0.548465657 -0.100637510 1.218538248 0.688866969
[91] 1.579129124 -0.108180577 -0.958228275 -1.376456532 -1.704818068
[96] -0.742028196 -1.454774477 -0.490975555 -1.015602075 -0.194111548
> colMin(tmp)
[1] -0.744403649 -0.933580925 -0.589925460 -0.574467203 -1.075860977
[6] -1.220145615 0.660435153 -0.744757181 0.137138128 -0.675909887
[11] 0.097653271 -1.287979171 -0.765995891 0.516109559 1.484669237
[16] -0.393475216 0.383462507 0.293164742 1.429658252 2.540223836
[21] -0.313305290 -0.469828846 0.219302992 0.466801024 0.125513438
[26] -0.839982743 0.214614851 0.007518155 0.806953023 0.587132039
[31] -1.676481837 0.999901847 1.305956609 0.131430106 -0.251904819
[36] 1.822088451 1.668619230 0.849101353 0.323234551 -1.077241876
[41] -1.782696246 -0.001262014 2.634765073 0.825036666 0.291661970
[46] 0.548204308 -0.139480178 0.320063466 -0.486473105 0.191993117
[51] 0.691638341 -0.662108615 0.330387900 -0.142410346 0.005868548
[56] -1.081719102 -1.245373266 -0.566688046 2.128663723 -1.314193365
[61] 0.120110543 1.111750667 0.834292854 1.939172780 -1.591232792
[66] 1.990882486 0.176456203 -0.286537559 0.208104236 0.534167829
[71] 0.145346556 -0.335194447 1.115444404 -0.978768086 -2.042583018
[76] -0.191708089 -1.333211777 0.146777437 -1.209961859 -0.847660747
[81] -2.468855346 0.359387166 3.304967337 -0.670903195 -0.918640559
[86] -0.392020248 -0.548465657 -0.100637510 1.218538248 0.688866969
[91] 1.579129124 -0.108180577 -0.958228275 -1.376456532 -1.704818068
[96] -0.742028196 -1.454774477 -0.490975555 -1.015602075 -0.194111548
> colMedians(tmp)
[1] -0.744403649 -0.933580925 -0.589925460 -0.574467203 -1.075860977
[6] -1.220145615 0.660435153 -0.744757181 0.137138128 -0.675909887
[11] 0.097653271 -1.287979171 -0.765995891 0.516109559 1.484669237
[16] -0.393475216 0.383462507 0.293164742 1.429658252 2.540223836
[21] -0.313305290 -0.469828846 0.219302992 0.466801024 0.125513438
[26] -0.839982743 0.214614851 0.007518155 0.806953023 0.587132039
[31] -1.676481837 0.999901847 1.305956609 0.131430106 -0.251904819
[36] 1.822088451 1.668619230 0.849101353 0.323234551 -1.077241876
[41] -1.782696246 -0.001262014 2.634765073 0.825036666 0.291661970
[46] 0.548204308 -0.139480178 0.320063466 -0.486473105 0.191993117
[51] 0.691638341 -0.662108615 0.330387900 -0.142410346 0.005868548
[56] -1.081719102 -1.245373266 -0.566688046 2.128663723 -1.314193365
[61] 0.120110543 1.111750667 0.834292854 1.939172780 -1.591232792
[66] 1.990882486 0.176456203 -0.286537559 0.208104236 0.534167829
[71] 0.145346556 -0.335194447 1.115444404 -0.978768086 -2.042583018
[76] -0.191708089 -1.333211777 0.146777437 -1.209961859 -0.847660747
[81] -2.468855346 0.359387166 3.304967337 -0.670903195 -0.918640559
[86] -0.392020248 -0.548465657 -0.100637510 1.218538248 0.688866969
[91] 1.579129124 -0.108180577 -0.958228275 -1.376456532 -1.704818068
[96] -0.742028196 -1.454774477 -0.490975555 -1.015602075 -0.194111548
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.7444036 -0.9335809 -0.5899255 -0.5744672 -1.075861 -1.220146 0.6604352
[2,] -0.7444036 -0.9335809 -0.5899255 -0.5744672 -1.075861 -1.220146 0.6604352
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.7447572 0.1371381 -0.6759099 0.09765327 -1.287979 -0.7659959 0.5161096
[2,] -0.7447572 0.1371381 -0.6759099 0.09765327 -1.287979 -0.7659959 0.5161096
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 1.484669 -0.3934752 0.3834625 0.2931647 1.429658 2.540224 -0.3133053
[2,] 1.484669 -0.3934752 0.3834625 0.2931647 1.429658 2.540224 -0.3133053
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.4698288 0.219303 0.466801 0.1255134 -0.8399827 0.2146149 0.007518155
[2,] -0.4698288 0.219303 0.466801 0.1255134 -0.8399827 0.2146149 0.007518155
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 0.806953 0.587132 -1.676482 0.9999018 1.305957 0.1314301 -0.2519048
[2,] 0.806953 0.587132 -1.676482 0.9999018 1.305957 0.1314301 -0.2519048
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 1.822088 1.668619 0.8491014 0.3232346 -1.077242 -1.782696 -0.001262014
[2,] 1.822088 1.668619 0.8491014 0.3232346 -1.077242 -1.782696 -0.001262014
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 2.634765 0.8250367 0.291662 0.5482043 -0.1394802 0.3200635 -0.4864731
[2,] 2.634765 0.8250367 0.291662 0.5482043 -0.1394802 0.3200635 -0.4864731
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 0.1919931 0.6916383 -0.6621086 0.3303879 -0.1424103 0.005868548 -1.081719
[2,] 0.1919931 0.6916383 -0.6621086 0.3303879 -0.1424103 0.005868548 -1.081719
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -1.245373 -0.566688 2.128664 -1.314193 0.1201105 1.111751 0.8342929
[2,] -1.245373 -0.566688 2.128664 -1.314193 0.1201105 1.111751 0.8342929
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 1.939173 -1.591233 1.990882 0.1764562 -0.2865376 0.2081042 0.5341678
[2,] 1.939173 -1.591233 1.990882 0.1764562 -0.2865376 0.2081042 0.5341678
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 0.1453466 -0.3351944 1.115444 -0.9787681 -2.042583 -0.1917081 -1.333212
[2,] 0.1453466 -0.3351944 1.115444 -0.9787681 -2.042583 -0.1917081 -1.333212
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 0.1467774 -1.209962 -0.8476607 -2.468855 0.3593872 3.304967 -0.6709032
[2,] 0.1467774 -1.209962 -0.8476607 -2.468855 0.3593872 3.304967 -0.6709032
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] -0.9186406 -0.3920202 -0.5484657 -0.1006375 1.218538 0.688867 1.579129
[2,] -0.9186406 -0.3920202 -0.5484657 -0.1006375 1.218538 0.688867 1.579129
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -0.1081806 -0.9582283 -1.376457 -1.704818 -0.7420282 -1.454774 -0.4909756
[2,] -0.1081806 -0.9582283 -1.376457 -1.704818 -0.7420282 -1.454774 -0.4909756
[,99] [,100]
[1,] -1.015602 -0.1941115
[2,] -1.015602 -0.1941115
>
>
> Max(tmp2)
[1] 2.798507
> Min(tmp2)
[1] -2.218508
> mean(tmp2)
[1] 0.03938881
> Sum(tmp2)
[1] 3.938881
> Var(tmp2)
[1] 0.994753
>
> rowMeans(tmp2)
[1] 0.6209332325 0.7548612105 0.5562812808 0.0003153504 0.6296626763
[6] 0.7582591556 0.8594456555 -2.0633144454 0.7890284259 0.0265203906
[11] -1.3046147542 0.4224300125 0.4852554658 1.4069001327 -1.6275750657
[16] -1.4446985432 0.6524392231 0.9238757478 -0.3252234642 -0.1641386888
[21] 1.1234036608 -0.9499103668 -1.0375602840 -1.5496914110 0.0379308274
[26] -2.2070522024 1.0710809328 2.7985070138 0.0463172992 -0.6759750820
[31] -0.6073070034 0.8765574062 0.1039107287 -0.9383188832 2.4606161981
[36] -0.8929009863 -1.7346723604 0.1247902786 -1.4481641471 -0.5539807242
[41] -1.2004830811 0.6402899011 0.3748618622 0.5682121085 -0.2393020325
[46] 0.3264143375 1.0171060272 -1.1191793618 -0.2200812557 -0.0590271371
[51] -0.8614164302 -0.1309621909 0.5769288107 0.5418523564 -1.2769023920
[56] 1.2273775632 -1.0850554158 1.1554935771 0.1299248429 -1.8636689849
[61] 0.6853004258 0.9986438529 0.6437851642 1.0569785626 -0.7325192391
[66] 0.4756440593 -0.0515801147 -1.0563770759 -2.2185083089 1.1251731433
[71] 1.2277355023 -0.3411994085 0.6682823412 1.0283290712 0.7872658002
[76] -0.2473688428 -0.0937676482 -0.4079256652 0.5970826988 -0.7543596162
[81] -0.3302988281 0.1997160773 0.6493511656 -0.0272049605 -0.0675958373
[86] -1.3563089178 0.1138304687 0.2743457981 -0.6097006379 1.1049107718
[91] 0.0842175418 -1.2824830755 1.8216591768 0.1617931442 1.1828825208
[96] 1.0239217874 1.4590272392 0.3134990423 0.3560423188 -1.0299449978
> rowSums(tmp2)
[1] 0.6209332325 0.7548612105 0.5562812808 0.0003153504 0.6296626763
[6] 0.7582591556 0.8594456555 -2.0633144454 0.7890284259 0.0265203906
[11] -1.3046147542 0.4224300125 0.4852554658 1.4069001327 -1.6275750657
[16] -1.4446985432 0.6524392231 0.9238757478 -0.3252234642 -0.1641386888
[21] 1.1234036608 -0.9499103668 -1.0375602840 -1.5496914110 0.0379308274
[26] -2.2070522024 1.0710809328 2.7985070138 0.0463172992 -0.6759750820
[31] -0.6073070034 0.8765574062 0.1039107287 -0.9383188832 2.4606161981
[36] -0.8929009863 -1.7346723604 0.1247902786 -1.4481641471 -0.5539807242
[41] -1.2004830811 0.6402899011 0.3748618622 0.5682121085 -0.2393020325
[46] 0.3264143375 1.0171060272 -1.1191793618 -0.2200812557 -0.0590271371
[51] -0.8614164302 -0.1309621909 0.5769288107 0.5418523564 -1.2769023920
[56] 1.2273775632 -1.0850554158 1.1554935771 0.1299248429 -1.8636689849
[61] 0.6853004258 0.9986438529 0.6437851642 1.0569785626 -0.7325192391
[66] 0.4756440593 -0.0515801147 -1.0563770759 -2.2185083089 1.1251731433
[71] 1.2277355023 -0.3411994085 0.6682823412 1.0283290712 0.7872658002
[76] -0.2473688428 -0.0937676482 -0.4079256652 0.5970826988 -0.7543596162
[81] -0.3302988281 0.1997160773 0.6493511656 -0.0272049605 -0.0675958373
[86] -1.3563089178 0.1138304687 0.2743457981 -0.6097006379 1.1049107718
[91] 0.0842175418 -1.2824830755 1.8216591768 0.1617931442 1.1828825208
[96] 1.0239217874 1.4590272392 0.3134990423 0.3560423188 -1.0299449978
> 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] 0.6209332325 0.7548612105 0.5562812808 0.0003153504 0.6296626763
[6] 0.7582591556 0.8594456555 -2.0633144454 0.7890284259 0.0265203906
[11] -1.3046147542 0.4224300125 0.4852554658 1.4069001327 -1.6275750657
[16] -1.4446985432 0.6524392231 0.9238757478 -0.3252234642 -0.1641386888
[21] 1.1234036608 -0.9499103668 -1.0375602840 -1.5496914110 0.0379308274
[26] -2.2070522024 1.0710809328 2.7985070138 0.0463172992 -0.6759750820
[31] -0.6073070034 0.8765574062 0.1039107287 -0.9383188832 2.4606161981
[36] -0.8929009863 -1.7346723604 0.1247902786 -1.4481641471 -0.5539807242
[41] -1.2004830811 0.6402899011 0.3748618622 0.5682121085 -0.2393020325
[46] 0.3264143375 1.0171060272 -1.1191793618 -0.2200812557 -0.0590271371
[51] -0.8614164302 -0.1309621909 0.5769288107 0.5418523564 -1.2769023920
[56] 1.2273775632 -1.0850554158 1.1554935771 0.1299248429 -1.8636689849
[61] 0.6853004258 0.9986438529 0.6437851642 1.0569785626 -0.7325192391
[66] 0.4756440593 -0.0515801147 -1.0563770759 -2.2185083089 1.1251731433
[71] 1.2277355023 -0.3411994085 0.6682823412 1.0283290712 0.7872658002
[76] -0.2473688428 -0.0937676482 -0.4079256652 0.5970826988 -0.7543596162
[81] -0.3302988281 0.1997160773 0.6493511656 -0.0272049605 -0.0675958373
[86] -1.3563089178 0.1138304687 0.2743457981 -0.6097006379 1.1049107718
[91] 0.0842175418 -1.2824830755 1.8216591768 0.1617931442 1.1828825208
[96] 1.0239217874 1.4590272392 0.3134990423 0.3560423188 -1.0299449978
> rowMin(tmp2)
[1] 0.6209332325 0.7548612105 0.5562812808 0.0003153504 0.6296626763
[6] 0.7582591556 0.8594456555 -2.0633144454 0.7890284259 0.0265203906
[11] -1.3046147542 0.4224300125 0.4852554658 1.4069001327 -1.6275750657
[16] -1.4446985432 0.6524392231 0.9238757478 -0.3252234642 -0.1641386888
[21] 1.1234036608 -0.9499103668 -1.0375602840 -1.5496914110 0.0379308274
[26] -2.2070522024 1.0710809328 2.7985070138 0.0463172992 -0.6759750820
[31] -0.6073070034 0.8765574062 0.1039107287 -0.9383188832 2.4606161981
[36] -0.8929009863 -1.7346723604 0.1247902786 -1.4481641471 -0.5539807242
[41] -1.2004830811 0.6402899011 0.3748618622 0.5682121085 -0.2393020325
[46] 0.3264143375 1.0171060272 -1.1191793618 -0.2200812557 -0.0590271371
[51] -0.8614164302 -0.1309621909 0.5769288107 0.5418523564 -1.2769023920
[56] 1.2273775632 -1.0850554158 1.1554935771 0.1299248429 -1.8636689849
[61] 0.6853004258 0.9986438529 0.6437851642 1.0569785626 -0.7325192391
[66] 0.4756440593 -0.0515801147 -1.0563770759 -2.2185083089 1.1251731433
[71] 1.2277355023 -0.3411994085 0.6682823412 1.0283290712 0.7872658002
[76] -0.2473688428 -0.0937676482 -0.4079256652 0.5970826988 -0.7543596162
[81] -0.3302988281 0.1997160773 0.6493511656 -0.0272049605 -0.0675958373
[86] -1.3563089178 0.1138304687 0.2743457981 -0.6097006379 1.1049107718
[91] 0.0842175418 -1.2824830755 1.8216591768 0.1617931442 1.1828825208
[96] 1.0239217874 1.4590272392 0.3134990423 0.3560423188 -1.0299449978
>
> colMeans(tmp2)
[1] 0.03938881
> colSums(tmp2)
[1] 3.938881
> colVars(tmp2)
[1] 0.994753
> colSd(tmp2)
[1] 0.997373
> colMax(tmp2)
[1] 2.798507
> colMin(tmp2)
[1] -2.218508
> colMedians(tmp2)
[1] 0.1193104
> colRanges(tmp2)
[,1]
[1,] -2.218508
[2,] 2.798507
>
> 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] -1.46300745 -0.06972237 -1.87674667 -0.57947182 0.55093973 -0.68424268
[7] -1.30205753 -6.73960997 -0.38799358 2.79533620
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.3053225
[2,] -0.8870300
[3,] -0.1877091
[4,] 0.3880234
[5,] 1.0681003
>
> rowApply(tmp,sum)
[1] -1.0742661 0.2612803 -5.9688812 -4.7797766 0.6367644 3.2094963
[7] -3.8075967 2.1348341 3.1845104 -3.5529410
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 8 2 5 7 4 1 9 1 9 10
[2,] 9 10 7 6 3 7 4 4 1 4
[3,] 4 7 10 8 5 2 3 3 7 5
[4,] 6 1 9 1 7 8 5 2 10 7
[5,] 10 3 8 4 9 9 6 7 5 1
[6,] 5 9 2 9 10 6 2 6 6 2
[7,] 3 6 3 2 6 4 10 5 3 8
[8,] 1 4 1 5 1 3 7 9 2 6
[9,] 2 8 4 10 2 5 1 10 4 3
[10,] 7 5 6 3 8 10 8 8 8 9
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -0.02044325 -4.35472919 1.49521536 1.65383083 5.58085193 -0.92776306
[7] -0.35618161 2.36995420 -1.34499187 -4.51263696 0.10906184 -2.52147870
[13] 1.09886566 -0.56270543 3.54341794 -3.16769664 1.44720644 -1.64135313
[19] 0.82524067 0.39631282
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.73955470
[2,] -0.42392304
[3,] -0.01299472
[4,] 0.35137995
[5,] 0.80464926
>
> rowApply(tmp,sum)
[1] 8.4412819 0.1728515 -2.1757736 -4.4718851 -2.8564970
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 7 17 11 14 10
[2,] 9 4 7 1 9
[3,] 19 12 5 12 18
[4,] 11 19 15 4 19
[5,] 18 18 19 15 16
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -0.01299472 0.2475990 1.5345885 0.7606590 1.3524150 1.7986575
[2,] 0.80464926 -0.9635359 0.2133299 1.1159787 0.9363161 0.3861806
[3,] -0.73955470 -0.8300432 -1.1063356 0.2499007 2.0567975 -1.2384705
[4,] 0.35137995 -2.2656371 0.1614663 -1.1741844 0.6360180 -1.3051737
[5,] -0.42392304 -0.5431119 0.6921663 0.7014767 0.5993054 -0.5689570
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.8707947 -0.3641490 0.74148749 -1.0410127 -0.77637574 0.7733941
[2,] -1.2010974 0.4786123 0.08330172 0.0212072 -1.50687569 0.3761455
[3,] -0.8938973 1.2640960 -1.60029152 -0.7724240 -0.05958702 -1.1637711
[4,] 1.4120547 0.8478378 0.19579694 -1.0809005 -0.23138617 -1.9150760
[5,] -0.5440363 0.1435571 -0.76528651 -1.6395070 2.68328646 -0.5921712
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 1.0772784 0.9761103 -0.1443756 0.1879217 0.9121896 -1.1202762
[2,] -0.4751586 -0.2429539 1.9307178 -2.1873619 0.3223153 0.1851006
[3,] 3.1354916 -1.5803947 0.2392777 -0.7515708 -0.8289156 0.9164287
[4,] -0.5803697 -0.1660475 0.8449171 0.6395701 0.6879931 -0.6392400
[5,] -2.0583760 0.4505804 0.6728810 -1.0562557 0.3536241 -0.9833662
[,19] [,20]
[1,] -0.4389474 1.1063181
[2,] -0.3051735 0.2011535
[3,] 1.7709506 -0.2434603
[4,] 0.1462865 -1.0371903
[5,] -0.3478754 0.3694919
>
>
> 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 : 563 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.22-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 -0.9375551 -0.7011925 1.299107 0.9824429 -1.358925 -0.6256632 1.269317
col8 col9 col10 col11 col12 col13 col14
row1 0.1060687 -0.7847783 -0.5965122 0.6021544 -0.6410398 -0.5984565 -1.961688
col15 col16 col17 col18 col19 col20
row1 0.2107455 -0.5375731 -1.076385 -1.035078 -0.8790159 0.3733038
> tmp[,"col10"]
col10
row1 -0.5965122
row2 -0.4041990
row3 1.4072350
row4 0.8975587
row5 -1.4842642
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 -0.9375551 -0.7011925 1.299107 0.9824429 -1.358925 -0.6256632 1.2693174
row5 -0.6701237 -0.2745672 1.418742 0.1734737 1.753529 -1.8901872 -0.8636213
col8 col9 col10 col11 col12 col13
row1 0.1060687 -0.7847783 -0.5965122 0.6021544 -0.6410398 -0.5984565
row5 -0.1429774 -0.3870984 -1.4842642 1.0656823 0.2754154 0.1811634
col14 col15 col16 col17 col18 col19
row1 -1.9616883 0.2107455 -0.5375731 -1.07638468 -1.0350781 -0.8790159
row5 -0.1933116 3.5304535 0.5424008 0.05180929 0.4594313 0.2085224
col20
row1 0.3733038
row5 0.4324431
> tmp[,c("col6","col20")]
col6 col20
row1 -0.62566316 0.3733038
row2 0.01357893 0.6933608
row3 -0.66833286 -0.7305197
row4 0.61231831 -1.7661939
row5 -1.89018718 0.4324431
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.6256632 0.3733038
row5 -1.8901872 0.4324431
>
>
>
>
> 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 52.33172 51.18279 47.7225 50.99736 48.83872 102.3192 50.20217 49.86061
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.29737 50.00185 51.47205 48.61423 50.42904 48.82769 50.52825 50.46616
col17 col18 col19 col20
row1 49.59502 50.70304 49.96341 104.5746
> tmp[,"col10"]
col10
row1 50.00185
row2 29.32320
row3 30.66276
row4 29.83470
row5 49.52299
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 52.33172 51.18279 47.72250 50.99736 48.83872 102.3192 50.20217 49.86061
row5 48.28955 50.44913 49.27332 48.71134 50.88893 103.7435 50.42123 49.23518
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.29737 50.00185 51.47205 48.61423 50.42904 48.82769 50.52825 50.46616
row5 50.76970 49.52299 49.11196 50.38290 47.80989 50.02057 50.34642 49.27536
col17 col18 col19 col20
row1 49.59502 50.70304 49.96341 104.5746
row5 48.79363 49.14982 51.61783 105.9028
> tmp[,c("col6","col20")]
col6 col20
row1 102.31915 104.57460
row2 74.11898 75.01524
row3 74.93248 73.93200
row4 75.58481 74.24653
row5 103.74353 105.90279
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 102.3192 104.5746
row5 103.7435 105.9028
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 102.3192 104.5746
row5 103.7435 105.9028
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -0.8113413
[2,] -1.2697015
[3,] -0.3205567
[4,] 0.4766975
[5,] -0.2297755
> tmp[,c("col17","col7")]
col17 col7
[1,] 2.42211948 -0.11209929
[2,] -0.69041782 0.46230686
[3,] 0.42270602 -0.83881351
[4,] -0.06673295 -0.34742649
[5,] 0.97947519 0.04267967
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.4722888 -0.1212389
[2,] -2.3453848 -1.7584508
[3,] 0.7737313 -0.2728787
[4,] 0.0129628 -1.9865434
[5,] -2.8163218 -1.0679423
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.4722888
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.4722888
[2,] -2.3453848
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6]
row3 0.07696788 -0.2898820 -0.5382093 -2.3730574 1.7074402 -1.0303963
row1 -1.87266866 0.1535011 -1.3709622 0.5997102 0.1538701 -0.2127407
[,7] [,8] [,9] [,10] [,11] [,12]
row3 -0.4457579 -0.7345359 -1.185686 0.03212547 0.1781394 -0.3921745
row1 0.6069529 0.5876940 -1.058391 -1.28519004 0.2977982 -0.6709796
[,13] [,14] [,15] [,16] [,17] [,18] [,19]
row3 2.4068443 0.4631119 1.0119534 0.5136229 -0.5878404 -0.9657482 0.9006613
row1 -0.6626225 -0.6488831 0.1130332 0.3043329 -1.7596588 0.7710692 0.3596151
[,20]
row3 -1.28133540
row1 -0.08895418
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 0.02077155 0.1229926 -0.6041409 -0.02968084 0.4343078 1.649221 0.2615817
[,8] [,9] [,10]
row2 0.4405663 -0.170478 -0.8872174
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 1.754531 0.7045694 1.027162 -0.3537078 0.9819139 -0.4642969 -0.8095554
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.4102869 1.363588 -0.4954356 -1.745848 -1.407162 -1.030831 0.4646254
[,15] [,16] [,17] [,18] [,19] [,20]
row5 1.795839 0.9681094 0.6258931 -1.791239 -0.2948416 1.415057
>
>
> 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: 0x600001590240>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMd90e1b310aa8"
[2] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMd90e30b2a98a"
[3] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMd90e2198bc00"
[4] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMd90e325eb53b"
[5] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMd90e67cc4e52"
[6] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMd90e162a1ebb"
[7] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMd90e2747925b"
[8] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMd90e4bd9a882"
[9] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMd90e3ec615b5"
[10] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMd90e3ebb3e45"
[11] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMd90e76f5442f"
[12] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMd90e604fa6ac"
[13] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMd90ed47979a"
[14] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMd90e57320645"
[15] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BMd90e1539c8bc"
>
>
> ### 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: 0x600001594d20>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x600001594d20>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x600001594d20>
> rowMedians(tmp)
[1] 0.1214985332 -0.3898491022 -0.0791517907 0.0803712807 0.2192091286
[6] -0.3703383205 0.2329276257 0.1182810642 -0.0210576958 0.0536703723
[11] 0.5551151830 -0.9059041081 -0.0347562135 0.3605198083 -0.2749088817
[16] -0.0275229422 0.0426426819 -0.1303044460 0.2101357791 0.6432199582
[21] 0.0385815110 -0.0587625530 0.0215862147 -0.1466595342 0.5476111583
[26] -0.3599749636 -0.2339896325 0.6230805456 -0.0087331782 0.0103862503
[31] 0.0746874720 -0.0046504449 -0.0066779742 -0.5249151117 0.0242265005
[36] 0.0567593992 0.2003130710 0.4895061871 0.0821556390 -0.0710378956
[41] 0.1063418695 0.2892796743 -0.3090926226 -0.3286060314 0.2730172933
[46] 0.1721319409 0.0701839842 0.1281367954 0.1496601102 -0.3010291128
[51] 0.0249109728 -0.7093439186 -0.2880029305 -0.2387172939 -0.2023804105
[56] -0.1975524296 0.1375997789 -0.3831666617 0.1501214412 0.2578713747
[61] -0.3690107691 0.4178713952 -0.2646832875 0.3176260667 -0.0487922790
[66] -0.5165629375 -0.1642795384 0.2732506847 0.2982890011 -0.3433196236
[71] 0.1555680361 -0.4738283044 -0.4521784235 0.2101794547 -0.1370999792
[76] -0.5662045290 0.4230793653 -0.3634016664 0.4495421289 0.5353527883
[81] 0.6114686446 0.2346875977 -0.5345285569 -0.4548012809 -0.5543935843
[86] 0.1695858526 0.1314609220 -0.6811959712 -0.0819267143 0.5935068006
[91] -0.4170996160 0.0021051337 0.5446165912 0.0333913775 -0.5355438752
[96] -0.1403270311 -0.2068980245 -0.1440112839 0.1397524083 0.0023794832
[101] -0.2831574293 -0.0851386285 0.2367922009 0.4213013521 -0.2456205639
[106] -0.0069883688 -0.3831962748 -0.2183527916 -0.1093131480 -0.0494311101
[111] -0.5807676748 0.0418591514 0.4122969531 -0.3320713090 -0.2887518572
[116] -0.1253697091 0.4061607114 -0.1310763441 0.2954096139 -0.0076365178
[121] 0.0155253316 -0.0032165662 -0.1367897955 0.3977303772 -0.0319313358
[126] 0.2383642600 0.0752480437 0.0014231881 -0.2031510530 0.0295749084
[131] 0.1014695033 0.2166063418 0.2437301156 0.2641914312 -0.3114834856
[136] 0.5895966991 -0.0701507187 0.5133448324 -0.0655315620 0.7030186079
[141] -0.2929273725 0.0829309836 -0.3801244525 0.1443776291 0.3418806852
[146] 0.3219567778 0.1753914393 -0.1179366248 0.0083659769 0.2349325777
[151] -0.3359478340 -0.3578482234 -0.1141265963 -0.0008204689 0.1852170224
[156] 0.2126397879 0.4004681578 0.6008437249 0.1108134224 -0.1137231542
[161] -0.0879637739 0.2050923803 0.2605783955 0.0119542071 -0.1285739181
[166] 0.1023844363 0.3907362311 -0.5492125352 -0.2540771749 0.0150652766
[171] -0.1924269670 -0.0352007097 0.0068007800 0.1470763951 0.0652299457
[176] -0.0606965296 0.7432326648 0.2694792048 0.6510048030 -0.0478238977
[181] -0.7348843166 -0.3504530124 0.3195835129 -0.4966479456 -0.3355373310
[186] -0.4520331386 -0.0825863609 0.2228823498 0.6036597188 -0.6042101510
[191] -0.1134862036 0.0047065440 0.0288223904 -0.1902799354 0.3686823742
[196] -0.0884514572 0.5256442604 0.0677351802 -0.3683251604 0.0435298913
[201] 0.4102156618 -0.2491798535 0.1391632468 -0.4408254697 -0.0400020567
[206] -0.0293712151 -0.0338156223 0.1357080921 -0.5603741458 0.1890256459
[211] -0.1959188973 0.1395605977 0.2870733797 0.2770979089 0.2022041373
[216] 0.1036073552 -0.0203463626 0.2786579820 0.3019882797 -0.1250496896
[221] -0.3340049748 -0.5547102805 -0.1379561745 0.0263303264 -0.5999076434
[226] -0.5030990908 0.0831686124 -0.0498595568 -0.1113230867 0.1354865855
>
> proc.time()
user system elapsed
0.625 2.881 3.753
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: 0x600003620000>
> .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: 0x600003620000>
> .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: 0x600003620000>
> .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: 0x600003620000>
> 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: 0x600003620780>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003620780>
> .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: 0x600003620780>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003620780>
> .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: 0x600003620780>
> 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: 0x600003620960>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003620960>
> .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: 0x600003620960>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600003620960>
> .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: 0x600003620960>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x600003620960>
> .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: 0x600003620960>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x600003620960>
> .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: 0x600003620960>
> 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: 0x600003620b40>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x600003620b40>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003620b40>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003620b40>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFiledadd386df830" "BufferedMatrixFiledadd7fc08546"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFiledadd386df830" "BufferedMatrixFiledadd7fc08546"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003620de0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003620de0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600003620de0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600003620de0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x600003620de0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x600003620de0>
> .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: 0x600003620fc0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003620fc0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600003620fc0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x600003620fc0>
> 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: 0x6000036211a0>
> .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: 0x6000036211a0>
> rm(P)
>
> proc.time()
user system elapsed
0.109 0.035 0.141
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
0.107 0.021 0.124