Ben Bolstad
| Snapshot Date: 2025-09-19 13:45 -0400 (Fri, 19 Sep 2025) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: devel |
| git_last_commit: 0147962 |
| git_last_commit_date: 2025-04-15 09:39:39 -0400 (Tue, 15 Apr 2025) |
| Back to Multiple platform build/check report for BioC 3.22: simplified long |
|
This page was generated on 2025-09-20 12:05 -0400 (Sat, 20 Sep 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 24.04.3 LTS) | x86_64 | 4.5.1 Patched (2025-08-23 r88802) -- "Great Square Root" | 4814 |
| lconway | macOS 12.7.1 Monterey | x86_64 | 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root" | 4603 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root" | 4547 |
| taishan | Linux (openEuler 24.03 LTS) | aarch64 | 4.5.0 (2025-04-11) -- "How About a Twenty-Six" | 4553 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
| Package 253/2333 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.73.0 (landing page) Ben Bolstad
| nebbiolo2 | Linux (Ubuntu 24.04.3 LTS) / x86_64 | OK | OK | OK | | ||||||||
| lconway | macOS 12.7.1 Monterey / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| kjohnson3 | macOS 13.7.7 Ventura / arm64 | OK | OK | WARNINGS | OK | | ||||||||
| taishan | Linux (openEuler 24.03 LTS) / aarch64 | OK | OK | OK | ||||||||||
|
To the developers/maintainers of the BufferedMatrix package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/BufferedMatrix.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
| Package: BufferedMatrix |
| Version: 1.73.0 |
| Command: /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings BufferedMatrix_1.73.0.tar.gz |
| StartedAt: 2025-09-19 18:30:32 -0400 (Fri, 19 Sep 2025) |
| EndedAt: 2025-09-19 18:30:48 -0400 (Fri, 19 Sep 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
0.119 0.040 0.155
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 Sep 19 18:30:41 2025"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Fri Sep 19 18:30:41 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: 0x600000758120>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Fri Sep 19 18:30:42 2025"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Fri Sep 19 18:30:42 2025"
>
> ColMode(tmp2)
<pointer: 0x600000758120>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 98.4940343 -0.8131666 -0.2211615 1.5117773
[2,] -0.4376631 -0.6164054 0.0470566 -0.5809539
[3,] -1.9425807 1.8409350 0.2222510 0.5459984
[4,] 0.2003128 1.6332755 -1.9327707 0.2884809
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 98.4940343 0.8131666 0.2211615 1.5117773
[2,] 0.4376631 0.6164054 0.0470566 0.5809539
[3,] 1.9425807 1.8409350 0.2222510 0.5459984
[4,] 0.2003128 1.6332755 1.9327707 0.2884809
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 9.9244161 0.9017575 0.4702781 1.2295436
[2,] 0.6615611 0.7851149 0.2169253 0.7622033
[3,] 1.3937649 1.3568106 0.4714351 0.7389171
[4,] 0.4475632 1.2779967 1.3902412 0.5371042
>
> my.function <- function(x,power){
+ (x+5)^power
+ }
>
> ewApply(tmp5,my.function,power=2)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 222.73820 34.83074 29.92394 38.80721
[2,] 32.05327 33.46755 27.21631 33.20299
[3,] 40.88023 40.40904 29.93660 32.93517
[4,] 29.67594 39.41324 40.83518 30.65952
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x600000744000>
> exp(tmp5)
<pointer: 0x600000744000>
> log(tmp5,2)
<pointer: 0x600000744000>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 463.6004
> Min(tmp5)
[1] 52.56316
> mean(tmp5)
[1] 73.41856
> Sum(tmp5)
[1] 14683.71
> Var(tmp5)
[1] 850.7236
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 91.25590 71.43038 74.05813 73.29610 69.78480 69.26394 68.81766 70.18365
[9] 73.00775 73.08724
> rowSums(tmp5)
[1] 1825.118 1428.608 1481.163 1465.922 1395.696 1385.279 1376.353 1403.673
[9] 1460.155 1461.745
> rowVars(tmp5)
[1] 7724.88666 107.20085 76.13061 95.85731 57.37577 77.23392
[7] 110.54228 64.80836 108.01533 82.97637
> rowSd(tmp5)
[1] 87.891334 10.353784 8.725286 9.790675 7.574680 8.788283 10.513909
[8] 8.050364 10.393042 9.109137
> rowMax(tmp5)
[1] 463.60037 93.42333 85.81602 85.53901 83.14487 88.73128 87.46505
[8] 83.14529 88.89580 92.65920
> rowMin(tmp5)
[1] 60.86465 53.65604 58.43805 57.29101 56.44752 57.75721 53.22037 52.83384
[9] 54.24572 52.56316
>
> colMeans(tmp5)
[1] 109.03405 75.41422 69.61931 66.56634 72.42867 74.40316 69.93362
[8] 70.66599 72.64953 63.37868 70.67576 69.65348 70.05750 77.60229
[15] 68.37872 66.41748 74.13877 71.25405 78.23612 77.86335
> colSums(tmp5)
[1] 1090.3405 754.1422 696.1931 665.6634 724.2867 744.0316 699.3362
[8] 706.6599 726.4953 633.7868 706.7576 696.5348 700.5750 776.0229
[15] 683.7872 664.1748 741.3877 712.5405 782.3612 778.6335
> colVars(tmp5)
[1] 15582.77257 23.66367 117.57323 58.12332 107.93803 50.51152
[7] 102.34955 66.45472 93.00110 17.78381 113.36942 87.53369
[13] 76.49003 115.28027 39.97074 84.63105 69.45159 74.74931
[19] 44.66743 73.04388
> colSd(tmp5)
[1] 124.830976 4.864532 10.843119 7.623865 10.389323 7.107146
[7] 10.116795 8.151976 9.643708 4.217086 10.647508 9.355944
[13] 8.745858 10.736865 6.322242 9.199514 8.333762 8.645768
[19] 6.683370 8.546571
> colMax(tmp5)
[1] 463.60037 84.10612 84.99308 80.77213 92.65920 85.35498 88.89580
[8] 80.22841 82.32213 68.74493 90.56859 83.17072 81.49257 93.42333
[15] 78.46314 82.41775 86.89545 82.57317 88.73128 90.12636
> colMin(tmp5)
[1] 60.45266 69.65833 52.56316 53.61676 59.64825 66.36379 53.65604 54.24572
[9] 53.22037 56.57859 59.02161 56.44752 57.61453 61.61856 58.42982 52.83384
[17] 61.57334 57.29101 69.49921 64.87782
>
>
> ### setting a random element to NA and then testing with na.rm=TRUE or na.rm=FALSE (The default)
>
>
> which.row <- sample(1:10,1,replace=TRUE)
> which.col <- sample(1:20,1,replace=TRUE)
>
> tmp5[which.row,which.col] <- NA
>
> Max(tmp5)
[1] NA
> Min(tmp5)
[1] NA
> mean(tmp5)
[1] NA
> Sum(tmp5)
[1] NA
> Var(tmp5)
[1] NA
>
> rowMeans(tmp5)
[1] NA 71.43038 74.05813 73.29610 69.78480 69.26394 68.81766 70.18365
[9] 73.00775 73.08724
> rowSums(tmp5)
[1] NA 1428.608 1481.163 1465.922 1395.696 1385.279 1376.353 1403.673
[9] 1460.155 1461.745
> rowVars(tmp5)
[1] 8144.47659 107.20085 76.13061 95.85731 57.37577 77.23392
[7] 110.54228 64.80836 108.01533 82.97637
> rowSd(tmp5)
[1] 90.246754 10.353784 8.725286 9.790675 7.574680 8.788283 10.513909
[8] 8.050364 10.393042 9.109137
> rowMax(tmp5)
[1] NA 93.42333 85.81602 85.53901 83.14487 88.73128 87.46505 83.14529
[9] 88.89580 92.65920
> rowMin(tmp5)
[1] NA 53.65604 58.43805 57.29101 56.44752 57.75721 53.22037 52.83384
[9] 54.24572 52.56316
>
> colMeans(tmp5)
[1] 109.03405 75.41422 69.61931 66.56634 72.42867 74.40316 69.93362
[8] 70.66599 72.64953 63.37868 70.67576 69.65348 70.05750 77.60229
[15] NA 66.41748 74.13877 71.25405 78.23612 77.86335
> colSums(tmp5)
[1] 1090.3405 754.1422 696.1931 665.6634 724.2867 744.0316 699.3362
[8] 706.6599 726.4953 633.7868 706.7576 696.5348 700.5750 776.0229
[15] NA 664.1748 741.3877 712.5405 782.3612 778.6335
> colVars(tmp5)
[1] 15582.77257 23.66367 117.57323 58.12332 107.93803 50.51152
[7] 102.34955 66.45472 93.00110 17.78381 113.36942 87.53369
[13] 76.49003 115.28027 NA 84.63105 69.45159 74.74931
[19] 44.66743 73.04388
> colSd(tmp5)
[1] 124.830976 4.864532 10.843119 7.623865 10.389323 7.107146
[7] 10.116795 8.151976 9.643708 4.217086 10.647508 9.355944
[13] 8.745858 10.736865 NA 9.199514 8.333762 8.645768
[19] 6.683370 8.546571
> colMax(tmp5)
[1] 463.60037 84.10612 84.99308 80.77213 92.65920 85.35498 88.89580
[8] 80.22841 82.32213 68.74493 90.56859 83.17072 81.49257 93.42333
[15] NA 82.41775 86.89545 82.57317 88.73128 90.12636
> colMin(tmp5)
[1] 60.45266 69.65833 52.56316 53.61676 59.64825 66.36379 53.65604 54.24572
[9] 53.22037 56.57859 59.02161 56.44752 57.61453 61.61856 NA 52.83384
[17] 61.57334 57.29101 69.49921 64.87782
>
> Max(tmp5,na.rm=TRUE)
[1] 463.6004
> Min(tmp5,na.rm=TRUE)
[1] 52.56316
> mean(tmp5,na.rm=TRUE)
[1] 73.39321
> Sum(tmp5,na.rm=TRUE)
[1] 14605.25
> Var(tmp5,na.rm=TRUE)
[1] 854.891
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.92920 71.43038 74.05813 73.29610 69.78480 69.26394 68.81766 70.18365
[9] 73.00775 73.08724
> rowSums(tmp5,na.rm=TRUE)
[1] 1746.655 1428.608 1481.163 1465.922 1395.696 1385.279 1376.353 1403.673
[9] 1460.155 1461.745
> rowVars(tmp5,na.rm=TRUE)
[1] 8144.47659 107.20085 76.13061 95.85731 57.37577 77.23392
[7] 110.54228 64.80836 108.01533 82.97637
> rowSd(tmp5,na.rm=TRUE)
[1] 90.246754 10.353784 8.725286 9.790675 7.574680 8.788283 10.513909
[8] 8.050364 10.393042 9.109137
> rowMax(tmp5,na.rm=TRUE)
[1] 463.60037 93.42333 85.81602 85.53901 83.14487 88.73128 87.46505
[8] 83.14529 88.89580 92.65920
> rowMin(tmp5,na.rm=TRUE)
[1] 60.86465 53.65604 58.43805 57.29101 56.44752 57.75721 53.22037 52.83384
[9] 54.24572 52.56316
>
> colMeans(tmp5,na.rm=TRUE)
[1] 109.03405 75.41422 69.61931 66.56634 72.42867 74.40316 69.93362
[8] 70.66599 72.64953 63.37868 70.67576 69.65348 70.05750 77.60229
[15] 67.25823 66.41748 74.13877 71.25405 78.23612 77.86335
> colSums(tmp5,na.rm=TRUE)
[1] 1090.3405 754.1422 696.1931 665.6634 724.2867 744.0316 699.3362
[8] 706.6599 726.4953 633.7868 706.7576 696.5348 700.5750 776.0229
[15] 605.3240 664.1748 741.3877 712.5405 782.3612 778.6335
> colVars(tmp5,na.rm=TRUE)
[1] 15582.77257 23.66367 117.57323 58.12332 107.93803 50.51152
[7] 102.34955 66.45472 93.00110 17.78381 113.36942 87.53369
[13] 76.49003 115.28027 30.84269 84.63105 69.45159 74.74931
[19] 44.66743 73.04388
> colSd(tmp5,na.rm=TRUE)
[1] 124.830976 4.864532 10.843119 7.623865 10.389323 7.107146
[7] 10.116795 8.151976 9.643708 4.217086 10.647508 9.355944
[13] 8.745858 10.736865 5.553619 9.199514 8.333762 8.645768
[19] 6.683370 8.546571
> colMax(tmp5,na.rm=TRUE)
[1] 463.60037 84.10612 84.99308 80.77213 92.65920 85.35498 88.89580
[8] 80.22841 82.32213 68.74493 90.56859 83.17072 81.49257 93.42333
[15] 72.64124 82.41775 86.89545 82.57317 88.73128 90.12636
> colMin(tmp5,na.rm=TRUE)
[1] 60.45266 69.65833 52.56316 53.61676 59.64825 66.36379 53.65604 54.24572
[9] 53.22037 56.57859 59.02161 56.44752 57.61453 61.61856 58.42982 52.83384
[17] 61.57334 57.29101 69.49921 64.87782
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] NaN 71.43038 74.05813 73.29610 69.78480 69.26394 68.81766 70.18365
[9] 73.00775 73.08724
> rowSums(tmp5,na.rm=TRUE)
[1] 0.000 1428.608 1481.163 1465.922 1395.696 1385.279 1376.353 1403.673
[9] 1460.155 1461.745
> rowVars(tmp5,na.rm=TRUE)
[1] NA 107.20085 76.13061 95.85731 57.37577 77.23392 110.54228
[8] 64.80836 108.01533 82.97637
> rowSd(tmp5,na.rm=TRUE)
[1] NA 10.353784 8.725286 9.790675 7.574680 8.788283 10.513909
[8] 8.050364 10.393042 9.109137
> rowMax(tmp5,na.rm=TRUE)
[1] NA 93.42333 85.81602 85.53901 83.14487 88.73128 87.46505 83.14529
[9] 88.89580 92.65920
> rowMin(tmp5,na.rm=TRUE)
[1] NA 53.65604 58.43805 57.29101 56.44752 57.75721 53.22037 52.83384
[9] 54.24572 52.56316
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 69.63779 75.73851 70.43448 64.98792 71.88738 75.01841 70.76811 69.60350
[9] 71.65513 63.21761 71.06287 70.63002 69.60763 77.22877 NaN 66.16647
[17] 74.70179 71.78588 78.95396 78.38810
> colSums(tmp5,na.rm=TRUE)
[1] 626.7401 681.6466 633.9104 584.8912 646.9864 675.1657 636.9130 626.4315
[9] 644.8961 568.9585 639.5658 635.6702 626.4687 695.0589 0.0000 595.4983
[17] 672.3161 646.0729 710.5857 705.4929
> colVars(tmp5,na.rm=TRUE)
[1] 69.88624 25.43855 124.79421 37.36033 118.13408 52.56698 107.30905
[8] 62.06159 93.50185 19.71492 125.85476 87.74712 83.77450 128.12071
[15] NA 94.50114 74.56691 80.91105 44.45376 79.07654
> colSd(tmp5,na.rm=TRUE)
[1] 8.359799 5.043664 11.171133 6.112310 10.868950 7.250309 10.359008
[8] 7.877918 9.669635 4.440149 11.218501 9.367343 9.152841 11.319042
[15] NA 9.721170 8.635214 8.995057 6.667365 8.892499
> colMax(tmp5,na.rm=TRUE)
[1] 85.08684 84.10612 84.99308 71.36288 92.65920 85.35498 88.89580 79.42739
[9] 82.32213 68.74493 90.56859 83.17072 81.49257 93.42333 -Inf 82.41775
[17] 86.89545 82.57317 88.73128 90.12636
> colMin(tmp5,na.rm=TRUE)
[1] 60.45266 69.65833 52.56316 53.61676 59.64825 66.36379 53.65604 54.24572
[9] 53.22037 56.57859 59.02161 56.44752 57.61453 61.61856 Inf 52.83384
[17] 61.57334 57.29101 69.49921 64.87782
>
>
>
>
> 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] 225.4639 165.8329 436.2039 209.4751 316.3601 184.1706 156.1585 233.2570
[9] 146.0425 177.8402
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 225.4639 165.8329 436.2039 209.4751 316.3601 184.1706 156.1585 233.2570
[9] 146.0425 177.8402
>
>
>
> 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] -1.989520e-13 -8.526513e-14 -2.842171e-14 0.000000e+00 -8.526513e-14
[6] 2.273737e-13 0.000000e+00 1.136868e-13 -4.263256e-13 8.526513e-14
[11] -1.989520e-13 -1.136868e-13 -5.684342e-14 1.136868e-13 0.000000e+00
[16] -1.989520e-13 1.705303e-13 0.000000e+00 1.136868e-13 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 6
2 1
3 9
5 7
5 6
2 2
5 14
4 1
1 12
6 9
6 5
2 8
5 3
2 10
5 18
4 1
2 13
5 13
6 18
5 13
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] 2.23595
> Min(tmp)
[1] -2.694494
> mean(tmp)
[1] 0.2169133
> Sum(tmp)
[1] 21.69133
> Var(tmp)
[1] 1.083151
>
> rowMeans(tmp)
[1] 0.2169133
> rowSums(tmp)
[1] 21.69133
> rowVars(tmp)
[1] 1.083151
> rowSd(tmp)
[1] 1.040745
> rowMax(tmp)
[1] 2.23595
> rowMin(tmp)
[1] -2.694494
>
> colMeans(tmp)
[1] -0.50959708 -1.24032319 1.35837338 -0.08324162 0.73502302 -1.30287693
[7] 0.05484463 0.99375962 -2.24506682 -0.11980705 -0.85261471 -2.69449394
[13] 1.08023977 1.41210618 0.49877259 0.28449157 -0.72498026 0.26773208
[19] -1.20037420 -1.09124894 -0.99485005 0.06864966 0.84033039 0.10570723
[25] 0.56062533 -2.07476252 0.35434233 0.16701421 1.43820381 1.89300808
[31] 0.85400376 1.10243458 2.15236727 0.21811274 0.89011378 -0.15946569
[37] 1.45343088 -0.29360095 0.16564558 0.73504613 1.39990015 2.23595047
[43] -0.62034753 0.27407026 -0.49168466 -0.42492774 1.22309819 -0.54938332
[49] 1.92538836 -1.74053369 -1.24520548 0.80416772 0.19292314 -1.48980948
[55] 0.20837888 0.28410632 1.52557878 0.87138596 0.15896155 0.63289578
[61] -0.64043687 -0.35763769 1.61566335 -0.78754864 -0.05858672 0.87917077
[67] 0.47066969 0.05801784 -0.55853385 1.39872438 -1.94540242 -0.06927837
[73] 0.05897844 0.08519753 1.59875917 1.85368844 1.36692347 -0.95391603
[79] 1.71059750 0.78139387 0.04782166 0.17897602 -0.31344895 0.72054624
[85] -1.72252616 1.48880503 0.47532119 -0.01963825 0.85108178 1.67370438
[91] -0.19734527 0.26613254 -1.05549416 0.91509337 1.19965199 1.00090519
[97] 0.77296713 0.50152213 -0.33185061 -0.53932279
> colSums(tmp)
[1] -0.50959708 -1.24032319 1.35837338 -0.08324162 0.73502302 -1.30287693
[7] 0.05484463 0.99375962 -2.24506682 -0.11980705 -0.85261471 -2.69449394
[13] 1.08023977 1.41210618 0.49877259 0.28449157 -0.72498026 0.26773208
[19] -1.20037420 -1.09124894 -0.99485005 0.06864966 0.84033039 0.10570723
[25] 0.56062533 -2.07476252 0.35434233 0.16701421 1.43820381 1.89300808
[31] 0.85400376 1.10243458 2.15236727 0.21811274 0.89011378 -0.15946569
[37] 1.45343088 -0.29360095 0.16564558 0.73504613 1.39990015 2.23595047
[43] -0.62034753 0.27407026 -0.49168466 -0.42492774 1.22309819 -0.54938332
[49] 1.92538836 -1.74053369 -1.24520548 0.80416772 0.19292314 -1.48980948
[55] 0.20837888 0.28410632 1.52557878 0.87138596 0.15896155 0.63289578
[61] -0.64043687 -0.35763769 1.61566335 -0.78754864 -0.05858672 0.87917077
[67] 0.47066969 0.05801784 -0.55853385 1.39872438 -1.94540242 -0.06927837
[73] 0.05897844 0.08519753 1.59875917 1.85368844 1.36692347 -0.95391603
[79] 1.71059750 0.78139387 0.04782166 0.17897602 -0.31344895 0.72054624
[85] -1.72252616 1.48880503 0.47532119 -0.01963825 0.85108178 1.67370438
[91] -0.19734527 0.26613254 -1.05549416 0.91509337 1.19965199 1.00090519
[97] 0.77296713 0.50152213 -0.33185061 -0.53932279
> 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] -0.50959708 -1.24032319 1.35837338 -0.08324162 0.73502302 -1.30287693
[7] 0.05484463 0.99375962 -2.24506682 -0.11980705 -0.85261471 -2.69449394
[13] 1.08023977 1.41210618 0.49877259 0.28449157 -0.72498026 0.26773208
[19] -1.20037420 -1.09124894 -0.99485005 0.06864966 0.84033039 0.10570723
[25] 0.56062533 -2.07476252 0.35434233 0.16701421 1.43820381 1.89300808
[31] 0.85400376 1.10243458 2.15236727 0.21811274 0.89011378 -0.15946569
[37] 1.45343088 -0.29360095 0.16564558 0.73504613 1.39990015 2.23595047
[43] -0.62034753 0.27407026 -0.49168466 -0.42492774 1.22309819 -0.54938332
[49] 1.92538836 -1.74053369 -1.24520548 0.80416772 0.19292314 -1.48980948
[55] 0.20837888 0.28410632 1.52557878 0.87138596 0.15896155 0.63289578
[61] -0.64043687 -0.35763769 1.61566335 -0.78754864 -0.05858672 0.87917077
[67] 0.47066969 0.05801784 -0.55853385 1.39872438 -1.94540242 -0.06927837
[73] 0.05897844 0.08519753 1.59875917 1.85368844 1.36692347 -0.95391603
[79] 1.71059750 0.78139387 0.04782166 0.17897602 -0.31344895 0.72054624
[85] -1.72252616 1.48880503 0.47532119 -0.01963825 0.85108178 1.67370438
[91] -0.19734527 0.26613254 -1.05549416 0.91509337 1.19965199 1.00090519
[97] 0.77296713 0.50152213 -0.33185061 -0.53932279
> colMin(tmp)
[1] -0.50959708 -1.24032319 1.35837338 -0.08324162 0.73502302 -1.30287693
[7] 0.05484463 0.99375962 -2.24506682 -0.11980705 -0.85261471 -2.69449394
[13] 1.08023977 1.41210618 0.49877259 0.28449157 -0.72498026 0.26773208
[19] -1.20037420 -1.09124894 -0.99485005 0.06864966 0.84033039 0.10570723
[25] 0.56062533 -2.07476252 0.35434233 0.16701421 1.43820381 1.89300808
[31] 0.85400376 1.10243458 2.15236727 0.21811274 0.89011378 -0.15946569
[37] 1.45343088 -0.29360095 0.16564558 0.73504613 1.39990015 2.23595047
[43] -0.62034753 0.27407026 -0.49168466 -0.42492774 1.22309819 -0.54938332
[49] 1.92538836 -1.74053369 -1.24520548 0.80416772 0.19292314 -1.48980948
[55] 0.20837888 0.28410632 1.52557878 0.87138596 0.15896155 0.63289578
[61] -0.64043687 -0.35763769 1.61566335 -0.78754864 -0.05858672 0.87917077
[67] 0.47066969 0.05801784 -0.55853385 1.39872438 -1.94540242 -0.06927837
[73] 0.05897844 0.08519753 1.59875917 1.85368844 1.36692347 -0.95391603
[79] 1.71059750 0.78139387 0.04782166 0.17897602 -0.31344895 0.72054624
[85] -1.72252616 1.48880503 0.47532119 -0.01963825 0.85108178 1.67370438
[91] -0.19734527 0.26613254 -1.05549416 0.91509337 1.19965199 1.00090519
[97] 0.77296713 0.50152213 -0.33185061 -0.53932279
> colMedians(tmp)
[1] -0.50959708 -1.24032319 1.35837338 -0.08324162 0.73502302 -1.30287693
[7] 0.05484463 0.99375962 -2.24506682 -0.11980705 -0.85261471 -2.69449394
[13] 1.08023977 1.41210618 0.49877259 0.28449157 -0.72498026 0.26773208
[19] -1.20037420 -1.09124894 -0.99485005 0.06864966 0.84033039 0.10570723
[25] 0.56062533 -2.07476252 0.35434233 0.16701421 1.43820381 1.89300808
[31] 0.85400376 1.10243458 2.15236727 0.21811274 0.89011378 -0.15946569
[37] 1.45343088 -0.29360095 0.16564558 0.73504613 1.39990015 2.23595047
[43] -0.62034753 0.27407026 -0.49168466 -0.42492774 1.22309819 -0.54938332
[49] 1.92538836 -1.74053369 -1.24520548 0.80416772 0.19292314 -1.48980948
[55] 0.20837888 0.28410632 1.52557878 0.87138596 0.15896155 0.63289578
[61] -0.64043687 -0.35763769 1.61566335 -0.78754864 -0.05858672 0.87917077
[67] 0.47066969 0.05801784 -0.55853385 1.39872438 -1.94540242 -0.06927837
[73] 0.05897844 0.08519753 1.59875917 1.85368844 1.36692347 -0.95391603
[79] 1.71059750 0.78139387 0.04782166 0.17897602 -0.31344895 0.72054624
[85] -1.72252616 1.48880503 0.47532119 -0.01963825 0.85108178 1.67370438
[91] -0.19734527 0.26613254 -1.05549416 0.91509337 1.19965199 1.00090519
[97] 0.77296713 0.50152213 -0.33185061 -0.53932279
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.5095971 -1.240323 1.358373 -0.08324162 0.735023 -1.302877 0.05484463
[2,] -0.5095971 -1.240323 1.358373 -0.08324162 0.735023 -1.302877 0.05484463
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.9937596 -2.245067 -0.119807 -0.8526147 -2.694494 1.08024 1.412106
[2,] 0.9937596 -2.245067 -0.119807 -0.8526147 -2.694494 1.08024 1.412106
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 0.4987726 0.2844916 -0.7249803 0.2677321 -1.200374 -1.091249 -0.99485
[2,] 0.4987726 0.2844916 -0.7249803 0.2677321 -1.200374 -1.091249 -0.99485
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 0.06864966 0.8403304 0.1057072 0.5606253 -2.074763 0.3543423 0.1670142
[2,] 0.06864966 0.8403304 0.1057072 0.5606253 -2.074763 0.3543423 0.1670142
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 1.438204 1.893008 0.8540038 1.102435 2.152367 0.2181127 0.8901138
[2,] 1.438204 1.893008 0.8540038 1.102435 2.152367 0.2181127 0.8901138
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -0.1594657 1.453431 -0.293601 0.1656456 0.7350461 1.3999 2.23595
[2,] -0.1594657 1.453431 -0.293601 0.1656456 0.7350461 1.3999 2.23595
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.6203475 0.2740703 -0.4916847 -0.4249277 1.223098 -0.5493833 1.925388
[2,] -0.6203475 0.2740703 -0.4916847 -0.4249277 1.223098 -0.5493833 1.925388
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -1.740534 -1.245205 0.8041677 0.1929231 -1.489809 0.2083789 0.2841063
[2,] -1.740534 -1.245205 0.8041677 0.1929231 -1.489809 0.2083789 0.2841063
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 1.525579 0.871386 0.1589615 0.6328958 -0.6404369 -0.3576377 1.615663
[2,] 1.525579 0.871386 0.1589615 0.6328958 -0.6404369 -0.3576377 1.615663
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -0.7875486 -0.05858672 0.8791708 0.4706697 0.05801784 -0.5585339 1.398724
[2,] -0.7875486 -0.05858672 0.8791708 0.4706697 0.05801784 -0.5585339 1.398724
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -1.945402 -0.06927837 0.05897844 0.08519753 1.598759 1.853688 1.366923
[2,] -1.945402 -0.06927837 0.05897844 0.08519753 1.598759 1.853688 1.366923
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -0.953916 1.710597 0.7813939 0.04782166 0.178976 -0.313449 0.7205462
[2,] -0.953916 1.710597 0.7813939 0.04782166 0.178976 -0.313449 0.7205462
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] -1.722526 1.488805 0.4753212 -0.01963825 0.8510818 1.673704 -0.1973453
[2,] -1.722526 1.488805 0.4753212 -0.01963825 0.8510818 1.673704 -0.1973453
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] 0.2661325 -1.055494 0.9150934 1.199652 1.000905 0.7729671 0.5015221
[2,] 0.2661325 -1.055494 0.9150934 1.199652 1.000905 0.7729671 0.5015221
[,99] [,100]
[1,] -0.3318506 -0.5393228
[2,] -0.3318506 -0.5393228
>
>
> Max(tmp2)
[1] 2.469663
> Min(tmp2)
[1] -2.527376
> mean(tmp2)
[1] 0.06992538
> Sum(tmp2)
[1] 6.992538
> Var(tmp2)
[1] 0.9411282
>
> rowMeans(tmp2)
[1] -0.45780924 0.62902954 2.46966280 -0.45176240 0.26569510 0.75578792
[7] 0.95496463 0.33076460 0.74081127 0.62245471 -1.07704533 -0.51955256
[13] 0.33278965 -0.14673731 0.51052555 -0.34944068 0.52014120 -0.29303645
[19] 0.30691062 0.16866130 0.55174655 1.26958123 0.18519795 1.53063839
[25] 0.88315400 -0.39730538 -0.06086613 0.01893459 -1.29843949 0.67807428
[31] 0.07675508 0.31711542 1.16664241 1.60357119 -1.27266583 -0.96990827
[37] -0.46391242 0.48596824 0.30041827 -0.80368746 -0.15881146 0.76407456
[43] -1.23328961 -0.37316445 -1.07320893 -0.09225312 0.83385681 -0.71683083
[49] 0.25094227 0.78113799 -0.84028541 -0.70774586 0.72212747 1.16681275
[55] -0.02917677 -0.80682779 -0.55076125 -0.51147777 0.96172058 -0.71364090
[61] -0.79868255 -0.88138351 -1.78088761 0.87592642 -2.05563654 0.63745354
[67] 0.25594923 -0.91368483 2.12300669 0.85455707 1.99298186 -1.05587174
[73] 0.98303177 -1.78282569 1.42065281 0.01116720 0.20740508 -0.59897143
[79] 0.22301224 -1.75143201 -0.68500634 -0.68169757 0.45479234 -2.52737587
[85] -1.52228542 1.36146523 -0.79862413 1.74763338 -0.63682959 0.03713696
[91] -0.50144004 0.59227397 2.06804380 1.04455900 -0.41729716 -0.35702031
[97] 0.89463394 0.86835502 0.92139453 0.37703217
> rowSums(tmp2)
[1] -0.45780924 0.62902954 2.46966280 -0.45176240 0.26569510 0.75578792
[7] 0.95496463 0.33076460 0.74081127 0.62245471 -1.07704533 -0.51955256
[13] 0.33278965 -0.14673731 0.51052555 -0.34944068 0.52014120 -0.29303645
[19] 0.30691062 0.16866130 0.55174655 1.26958123 0.18519795 1.53063839
[25] 0.88315400 -0.39730538 -0.06086613 0.01893459 -1.29843949 0.67807428
[31] 0.07675508 0.31711542 1.16664241 1.60357119 -1.27266583 -0.96990827
[37] -0.46391242 0.48596824 0.30041827 -0.80368746 -0.15881146 0.76407456
[43] -1.23328961 -0.37316445 -1.07320893 -0.09225312 0.83385681 -0.71683083
[49] 0.25094227 0.78113799 -0.84028541 -0.70774586 0.72212747 1.16681275
[55] -0.02917677 -0.80682779 -0.55076125 -0.51147777 0.96172058 -0.71364090
[61] -0.79868255 -0.88138351 -1.78088761 0.87592642 -2.05563654 0.63745354
[67] 0.25594923 -0.91368483 2.12300669 0.85455707 1.99298186 -1.05587174
[73] 0.98303177 -1.78282569 1.42065281 0.01116720 0.20740508 -0.59897143
[79] 0.22301224 -1.75143201 -0.68500634 -0.68169757 0.45479234 -2.52737587
[85] -1.52228542 1.36146523 -0.79862413 1.74763338 -0.63682959 0.03713696
[91] -0.50144004 0.59227397 2.06804380 1.04455900 -0.41729716 -0.35702031
[97] 0.89463394 0.86835502 0.92139453 0.37703217
> 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] -0.45780924 0.62902954 2.46966280 -0.45176240 0.26569510 0.75578792
[7] 0.95496463 0.33076460 0.74081127 0.62245471 -1.07704533 -0.51955256
[13] 0.33278965 -0.14673731 0.51052555 -0.34944068 0.52014120 -0.29303645
[19] 0.30691062 0.16866130 0.55174655 1.26958123 0.18519795 1.53063839
[25] 0.88315400 -0.39730538 -0.06086613 0.01893459 -1.29843949 0.67807428
[31] 0.07675508 0.31711542 1.16664241 1.60357119 -1.27266583 -0.96990827
[37] -0.46391242 0.48596824 0.30041827 -0.80368746 -0.15881146 0.76407456
[43] -1.23328961 -0.37316445 -1.07320893 -0.09225312 0.83385681 -0.71683083
[49] 0.25094227 0.78113799 -0.84028541 -0.70774586 0.72212747 1.16681275
[55] -0.02917677 -0.80682779 -0.55076125 -0.51147777 0.96172058 -0.71364090
[61] -0.79868255 -0.88138351 -1.78088761 0.87592642 -2.05563654 0.63745354
[67] 0.25594923 -0.91368483 2.12300669 0.85455707 1.99298186 -1.05587174
[73] 0.98303177 -1.78282569 1.42065281 0.01116720 0.20740508 -0.59897143
[79] 0.22301224 -1.75143201 -0.68500634 -0.68169757 0.45479234 -2.52737587
[85] -1.52228542 1.36146523 -0.79862413 1.74763338 -0.63682959 0.03713696
[91] -0.50144004 0.59227397 2.06804380 1.04455900 -0.41729716 -0.35702031
[97] 0.89463394 0.86835502 0.92139453 0.37703217
> rowMin(tmp2)
[1] -0.45780924 0.62902954 2.46966280 -0.45176240 0.26569510 0.75578792
[7] 0.95496463 0.33076460 0.74081127 0.62245471 -1.07704533 -0.51955256
[13] 0.33278965 -0.14673731 0.51052555 -0.34944068 0.52014120 -0.29303645
[19] 0.30691062 0.16866130 0.55174655 1.26958123 0.18519795 1.53063839
[25] 0.88315400 -0.39730538 -0.06086613 0.01893459 -1.29843949 0.67807428
[31] 0.07675508 0.31711542 1.16664241 1.60357119 -1.27266583 -0.96990827
[37] -0.46391242 0.48596824 0.30041827 -0.80368746 -0.15881146 0.76407456
[43] -1.23328961 -0.37316445 -1.07320893 -0.09225312 0.83385681 -0.71683083
[49] 0.25094227 0.78113799 -0.84028541 -0.70774586 0.72212747 1.16681275
[55] -0.02917677 -0.80682779 -0.55076125 -0.51147777 0.96172058 -0.71364090
[61] -0.79868255 -0.88138351 -1.78088761 0.87592642 -2.05563654 0.63745354
[67] 0.25594923 -0.91368483 2.12300669 0.85455707 1.99298186 -1.05587174
[73] 0.98303177 -1.78282569 1.42065281 0.01116720 0.20740508 -0.59897143
[79] 0.22301224 -1.75143201 -0.68500634 -0.68169757 0.45479234 -2.52737587
[85] -1.52228542 1.36146523 -0.79862413 1.74763338 -0.63682959 0.03713696
[91] -0.50144004 0.59227397 2.06804380 1.04455900 -0.41729716 -0.35702031
[97] 0.89463394 0.86835502 0.92139453 0.37703217
>
> colMeans(tmp2)
[1] 0.06992538
> colSums(tmp2)
[1] 6.992538
> colVars(tmp2)
[1] 0.9411282
> colSd(tmp2)
[1] 0.9701176
> colMax(tmp2)
[1] 2.469663
> colMin(tmp2)
[1] -2.527376
> colMedians(tmp2)
[1] 0.1769296
> colRanges(tmp2)
[,1]
[1,] -2.527376
[2,] 2.469663
>
> 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] 1.1736802 -1.6348295 3.9896308 0.3650587 4.9606345 2.9425435
[7] 4.9699143 0.2480915 -4.5322024 1.6542439
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.49302500
[2,] -0.38836422
[3,] 0.03440932
[4,] 0.70560640
[5,] 2.17537049
>
> rowApply(tmp,sum)
[1] 2.21622884 2.98090252 -0.07910271 -0.88890812 2.42668581 -2.20886586
[7] 3.12789486 0.65659359 4.09096286 1.81437372
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 5 6 2 4 8 2 5 9 2 10
[2,] 4 1 4 10 10 1 7 4 4 6
[3,] 10 7 7 8 1 10 6 1 7 8
[4,] 2 9 6 2 3 9 2 5 1 7
[5,] 1 4 9 6 5 8 8 7 6 9
[6,] 8 3 8 9 6 6 9 3 9 4
[7,] 7 10 10 1 9 7 3 2 10 1
[8,] 3 8 1 3 4 4 10 8 5 5
[9,] 9 2 3 5 2 5 1 6 3 2
[10,] 6 5 5 7 7 3 4 10 8 3
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 1.42547124 -0.50035291 -0.76574403 2.46029494 -1.93024309 -0.67076180
[7] 2.71979742 -0.55732711 -2.98368617 1.75540608 1.88175854 0.02638778
[13] -0.43739298 -2.69572819 -0.80707067 2.81534516 0.56630363 0.24745157
[19] 2.10032028 -0.31081276
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.59306615
[2,] -0.59100887
[3,] 0.05622986
[4,] 1.52294819
[5,] 2.03036821
>
> rowApply(tmp,sum)
[1] 3.987734 2.291152 1.991833 -7.314255 3.382953
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 19 20 10 3 5
[2,] 17 10 16 1 6
[3,] 11 2 15 18 4
[4,] 9 14 18 9 17
[5,] 7 6 13 6 7
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 2.03036821 1.1262216 -0.06311985 -0.3218300 -0.4704997 2.27706912
[2,] 1.52294819 0.1144326 -1.53974556 0.7135640 -0.4115974 -1.06321797
[3,] 0.05622986 0.8633762 0.74470288 1.1936453 0.3352517 0.06062003
[4,] -1.59306615 -2.1220506 0.82923887 -0.3172547 -1.1139636 -1.83760311
[5,] -0.59100887 -0.4823326 -0.73682038 1.1921702 -0.2694341 -0.10762987
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.3878398 -0.5085407 -1.1476999 1.1975026 -0.58604033 0.9723792
[2,] 0.2305125 -1.6935312 0.7840068 1.0167721 -0.05539965 -0.1346329
[3,] 1.7849048 -0.2212861 -0.5630161 -0.8775200 2.13219036 -1.6847212
[4,] -0.1715129 1.0926299 -1.0621928 -0.1541993 0.36885838 0.1303553
[5,] 0.4880533 0.7734010 -0.9947842 0.5728507 0.02214977 0.7430072
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.78777513 -0.3676746 1.0917845 -0.6177802 0.9549616 -1.79786734
[2,] -0.09618757 0.5662584 0.1962743 1.3707526 -0.8047578 1.36343853
[3,] -0.23894415 -0.3772278 0.6357933 1.1680090 -0.8996204 0.10122603
[4,] -0.61713951 -1.1279860 -1.3655202 0.4642374 -0.2295158 0.49071143
[5,] 1.30265338 -1.3890981 -1.3654026 0.4301264 1.5452361 0.08994291
[,19] [,20]
[1,] -0.1524079 0.7708432
[2,] 1.3837085 -1.1724467
[3,] -0.6066156 -1.6151650
[4,] -0.2194094 1.2411279
[5,] 1.6950447 0.4648278
>
>
> 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 0.7352915 -1.262919 -0.06965699 -1.134155 0.1280831 -0.0979327 -1.034513
col8 col9 col10 col11 col12 col13 col14
row1 0.8028686 1.332241 0.4121713 0.7324939 0.8359541 -2.311773 -0.1818969
col15 col16 col17 col18 col19 col20
row1 -0.2055507 -1.09875 -0.2738854 -0.3164875 -0.3771207 -0.8501437
> tmp[,"col10"]
col10
row1 0.4121713
row2 -1.6170998
row3 -0.3664785
row4 -0.5509791
row5 -0.7268585
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 0.7352915 -1.26291867 -0.06965699 -1.134155 0.1280831 -0.09793270
row5 0.6750962 0.06050806 0.29826648 -1.108576 -0.8697311 0.07166399
col7 col8 col9 col10 col11 col12 col13
row1 -1.0345127 0.8028686 1.332241 0.4121713 0.7324939 0.8359541 -2.3117726
row5 -0.2141389 0.2983530 -1.143311 -0.7268585 0.9042152 -0.3786856 0.8609369
col14 col15 col16 col17 col18 col19
row1 -0.1818969 -0.2055507 -1.09875018 -0.2738854 -0.3164875 -0.3771207
row5 1.3117521 1.1470421 -0.08799457 0.3802101 -0.3158405 0.7726914
col20
row1 -0.8501437
row5 -1.7278596
> tmp[,c("col6","col20")]
col6 col20
row1 -0.09793270 -0.8501437
row2 -0.50628693 -1.4562012
row3 0.48071995 -1.6658622
row4 0.67794233 1.3129194
row5 0.07166399 -1.7278596
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.09793270 -0.8501437
row5 0.07166399 -1.7278596
>
>
>
>
> 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 51.37702 50.22171 49.38224 50.22278 49.29903 104.6993 49.73563 50.57602
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.63775 48.42586 49.01586 50.22068 50.08897 49.02512 50.33522 50.51901
col17 col18 col19 col20
row1 49.35614 50.83241 50.50412 104.6624
> tmp[,"col10"]
col10
row1 48.42586
row2 29.21662
row3 28.78897
row4 28.85855
row5 50.32119
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 51.37702 50.22171 49.38224 50.22278 49.29903 104.6993 49.73563 50.57602
row5 51.60767 48.42436 50.11354 50.71487 50.92611 102.9011 50.11385 49.14139
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.63775 48.42586 49.01586 50.22068 50.08897 49.02512 50.33522 50.51901
row5 50.16633 50.32119 49.19304 49.82068 49.35351 50.53181 48.62732 48.78410
col17 col18 col19 col20
row1 49.35614 50.83241 50.50412 104.6624
row5 48.62632 50.92763 51.89447 106.5664
> tmp[,c("col6","col20")]
col6 col20
row1 104.69935 104.66237
row2 75.62182 75.31991
row3 74.31839 74.44906
row4 76.22056 75.63927
row5 102.90109 106.56645
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.6993 104.6624
row5 102.9011 106.5664
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.6993 104.6624
row5 102.9011 106.5664
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.08568707
[2,] -0.58090002
[3,] -2.00035279
[4,] 1.51031170
[5,] 1.52158424
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.07859787 0.5615990
[2,] -0.34211819 0.1599449
[3,] 0.98781682 -0.5448030
[4,] 0.42603880 1.8702563
[5,] 0.26543629 -1.5986028
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -1.2466859 -0.4094039
[2,] 0.8334414 0.3191820
[3,] 1.6474018 -0.8129737
[4,] 0.3708992 -0.5395591
[5,] 1.3079089 -0.4541694
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -1.246686
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -1.2466859
[2,] 0.8334414
>
>
>
> 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 -0.6508939 -1.341847 0.06922037 -0.3160805 0.633601 0.03573968
row1 -0.4538168 -1.103554 -0.65138321 1.2698957 -1.735413 -0.23863336
[,7] [,8] [,9] [,10] [,11] [,12]
row3 -0.6094808 0.55044281 -0.1022105 -0.3325176 0.3806278 -0.2400584
row1 -1.4686412 -0.06404586 0.4689262 -0.1776717 0.5347047 -1.8712069
[,13] [,14] [,15] [,16] [,17] [,18]
row3 -1.8663956 0.5452947 -0.6279783 0.4151052 -0.02238263 0.4146535
row1 0.4377945 0.5336625 0.9413440 1.0719369 1.61263734 -0.9373525
[,19] [,20]
row3 0.09338214 0.3033851
row1 -0.30308955 -0.3472361
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 0.5565831 0.8931821 -0.5037844 0.2057268 0.9659721 -0.4402871 2.416032
[,8] [,9] [,10]
row2 -0.8503823 -1.916336 -1.016128
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.9416107 -0.4092195 0.3943216 0.3627283 0.4454367 -0.08805386 -0.2883189
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.5563642 0.6133629 -1.353329 1.158283 -0.5299723 1.865184 -0.5193027
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -1.613977 1.126153 -2.291988 -0.4287029 0.02606347 -0.9467049
>
>
> 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: 0x6000007400c0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM7d7825244513"
[2] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM7d787032f571"
[3] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM7d7821900743"
[4] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM7d7876ccd0eb"
[5] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM7d78a8313c"
[6] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM7d7822385a7a"
[7] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM7d7821bc1123"
[8] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM7d7842092222"
[9] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM7d7865a0080c"
[10] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM7d786d707ff3"
[11] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM7d7874e062a6"
[12] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM7d78376cbc3c"
[13] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM7d7843ba2391"
[14] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM7d7871752753"
[15] "/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM7d784268f456"
>
>
> ### 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: 0x6000007702a0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x6000007702a0>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x6000007702a0>
> rowMedians(tmp)
[1] -0.256252105 0.564192834 0.069417360 -0.332541209 -0.622380010
[6] 0.197695129 -0.365865235 -0.232828522 -0.171474455 0.144662094
[11] 0.035355442 0.057515360 0.395992442 -0.265010199 0.156042807
[16] 0.224791554 0.410151156 0.676946351 -0.374245748 -0.275501579
[21] -0.194081930 0.073331390 0.312063386 0.790963219 0.498165281
[26] -0.265479048 -0.095497738 -0.147996393 -0.118873876 -0.247214184
[31] 0.628019355 -0.009417760 -0.188522061 0.244521879 -0.700978282
[36] -0.097339547 -0.408708537 -0.143036625 -0.503126601 0.392106291
[41] 0.043017240 0.032301270 -0.024142929 0.476044197 -0.403422423
[46] 0.599974700 0.285049866 0.502520238 0.126036249 0.048126436
[51] 0.242103917 -0.064287705 -0.159963210 0.402259085 0.110802458
[56] 0.093775105 0.193781811 -0.306712421 0.228051581 -0.433851750
[61] 0.654076151 -0.237355573 -0.159228641 0.001072640 -0.080529243
[66] 0.531000919 -0.213050698 0.752943253 -0.124474563 0.179380768
[71] 0.103948972 -0.277489112 0.036383492 -0.376674901 -0.159597386
[76] 0.362772856 -0.416476639 0.705807984 0.306757347 -0.270274713
[81] -0.217705821 0.650563732 -0.032833352 0.373053593 -0.033398283
[86] -0.043247767 0.477225841 0.107826545 0.374746469 0.051122212
[91] 0.080211848 -0.021695224 0.697646310 -0.027478769 0.065143608
[96] -0.112931088 0.446247010 0.283904914 -0.394324121 0.087415106
[101] -0.292861357 0.387461090 0.152136641 -0.322271482 0.175719018
[106] 0.369986129 0.081692852 -0.213765617 -0.369855297 -0.417624580
[111] 0.039369729 -0.362809537 -0.036621824 0.214122068 0.219369829
[116] 0.042500532 -0.351279467 0.102562571 -0.093845579 -0.131721024
[121] -0.259281259 0.003977669 -0.112866489 0.270589706 0.086032429
[126] -0.169659666 0.362349553 0.276379041 0.269307589 0.066269184
[131] 0.238299676 -0.177185293 -0.714455598 -0.222860859 0.169748348
[136] 0.316174204 0.043373403 0.419380240 -0.085836360 0.045604948
[141] 0.112910238 -0.287650349 0.429273985 -0.237831318 -0.239438368
[146] -0.185392928 0.013436637 -0.528406936 0.121460984 -0.076640446
[151] 0.617813776 0.068201664 -0.295356729 0.222706464 -0.261142648
[156] 0.236360026 -0.201697195 0.159903733 -0.176869448 -0.701671142
[161] 0.299464755 0.412001698 -0.050022592 0.358711685 0.232012915
[166] 0.212493077 -0.385268596 -0.068957791 0.642747160 0.126693534
[171] 0.119045209 -0.133080834 0.069335768 0.344514166 0.612973474
[176] 0.256113024 -0.270786848 0.362196981 -0.085950289 0.525355334
[181] 0.475678744 0.194169756 0.320035194 0.198634829 0.379898018
[186] 0.021578100 0.232022374 -0.082181857 -0.127353054 -0.055531196
[191] -0.318088560 0.160548458 -0.054480896 0.101553534 -0.060252796
[196] 0.659141994 0.540719007 -0.522177375 -0.297326038 0.179929997
[201] 0.047049174 -0.128662094 -0.156386160 0.748115951 0.317764561
[206] 0.246345177 0.343972362 0.120076474 -0.124536678 -0.293827571
[211] 0.439794515 -0.314392827 -0.330340050 -0.158029166 -0.227548970
[216] 0.267885199 -0.081679999 -0.080611527 -0.077282350 0.089073137
[221] 0.533090003 -0.028285539 -0.171165356 0.143026781 -0.302968355
[226] -0.361749574 -0.421972420 0.105320271 0.294031399 0.157447828
>
> proc.time()
user system elapsed
0.629 3.133 4.005
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: 0x600000424000>
> .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: 0x600000424000>
> .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: 0x600000424000>
> .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: 0x600000424000>
> 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: 0x6000004281e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000004281e0>
> .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: 0x6000004281e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000004281e0>
> .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: 0x6000004281e0>
> 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: 0x6000004283c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000004283c0>
> .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: 0x6000004283c0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x6000004283c0>
> .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: 0x6000004283c0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x6000004283c0>
> .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: 0x6000004283c0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x6000004283c0>
> .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: 0x6000004283c0>
> 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: 0x6000004285a0>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x6000004285a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000004285a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000004285a0>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile7fed31ed7dbd" "BufferedMatrixFile7fed5eda1ce6"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile7fed31ed7dbd" "BufferedMatrixFile7fed5eda1ce6"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x600000428840>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600000428840>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600000428840>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600000428840>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x600000428840>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x600000428840>
> .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: 0x600000428a20>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600000428a20>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600000428a20>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x600000428a20>
> 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: 0x600000428c00>
> .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: 0x600000428c00>
> rm(P)
>
> proc.time()
user system elapsed
0.130 0.047 0.172
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
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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.
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> 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
0.106 0.020 0.123