Ben Bolstad
| Snapshot Date: 2025-04-21 13:40 -0400 (Mon, 21 Apr 2025) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: RELEASE_3_21 |
| git_last_commit: aa9e634 |
| git_last_commit_date: 2025-04-15 09:39:39 -0400 (Tue, 15 Apr 2025) |
| Back to Multiple platform build/check report for BioC 3.21: simplified long |
|
This page was generated on 2025-04-22 13:15 -0400 (Tue, 22 Apr 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 24.04.1 LTS) | x86_64 | 4.5.0 RC (2025-04-04 r88126) -- "How About a Twenty-Six" | 4831 |
| palomino7 | Windows Server 2022 Datacenter | x64 | 4.5.0 RC (2025-04-04 r88126 ucrt) -- "How About a Twenty-Six" | 4573 |
| lconway | macOS 12.7.1 Monterey | x86_64 | 4.5.0 RC (2025-04-04 r88126) -- "How About a Twenty-Six" | 4599 |
| kjohnson3 | macOS 13.7.1 Ventura | arm64 | 4.5.0 RC (2025-04-04 r88126) -- "How About a Twenty-Six" | 4553 |
| kunpeng2 | Linux (openEuler 24.03 LTS) | aarch64 | R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences" | 4570 |
| 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 252/2341 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.72.0 (landing page) Ben Bolstad
| nebbiolo1 | Linux (Ubuntu 24.04.1 LTS) / x86_64 | OK | OK | OK | | ||||||||
| palomino7 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | | ||||||||
| lconway | macOS 12.7.1 Monterey / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| kjohnson3 | macOS 13.7.1 Ventura / arm64 | OK | OK | WARNINGS | OK | | ||||||||
| kunpeng2 | 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: 1.72.0 |
| 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_1.72.0.tar.gz |
| StartedAt: 2025-04-21 19:29:55 -0400 (Mon, 21 Apr 2025) |
| EndedAt: 2025-04-21 19:30:48 -0400 (Mon, 21 Apr 2025) |
| EllapsedTime: 52.6 seconds |
| RetCode: 0 |
| Status: WARNINGS |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 1 |
##############################################################################
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###
### 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_1.72.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.5.0 RC (2025-04-04 r88126)
* using platform: x86_64-apple-darwin20
* R was compiled by
Apple clang version 14.0.0 (clang-1400.0.29.202)
GNU Fortran (GCC) 14.2.0
* running under: macOS Monterey 12.7.6
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.72.0’
* 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-3.21-bioc/meat/BufferedMatrix.Rcheck/00install.out’ for details.
* used C compiler: ‘Apple clang version 14.0.0 (clang-1400.0.29.202)’
* used SDK: ‘MacOSX11.3.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-3.21-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/Library/Frameworks/R.framework/Versions/4.5-x86_64/Resources/library’
* installing *source* package ‘BufferedMatrix’ ...
** this is package ‘BufferedMatrix’ version ‘1.72.0’
** using staged installation
** libs
using C compiler: ‘Apple clang version 14.0.0 (clang-1400.0.29.202)’
using SDK: ‘MacOSX11.3.sdk’
clang -arch x86_64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/x86_64/include -fPIC -falign-functions=64 -Wall -g -O2 -c RBufferedMatrix.c -o RBufferedMatrix.o
clang -arch x86_64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/x86_64/include -fPIC -falign-functions=64 -Wall -g -O2 -c doubleBufferedMatrix.c -o doubleBufferedMatrix.o
doubleBufferedMatrix.c:1580:7: warning: logical not is only applied to the left hand side of this bitwise operator [-Wlogical-not-parentheses]
if (!(Matrix->readonly) & setting){
^ ~
doubleBufferedMatrix.c:1580:7: note: add parentheses after the '!' to evaluate the bitwise operator first
if (!(Matrix->readonly) & setting){
^
( )
doubleBufferedMatrix.c:1580:7: note: add parentheses around left hand side expression to silence this warning
if (!(Matrix->readonly) & setting){
^
( )
doubleBufferedMatrix.c:3327:12: warning: unused function 'sort_double' [-Wunused-function]
static int sort_double(const double *a1,const double *a2){
^
2 warnings generated.
clang -arch x86_64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/x86_64/include -fPIC -falign-functions=64 -Wall -g -O2 -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
clang -arch x86_64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG -I/opt/R/x86_64/include -fPIC -falign-functions=64 -Wall -g -O2 -c init_package.c -o init_package.o
clang -arch x86_64 -dynamiclib -Wl,-headerpad_max_install_names -undefined dynamic_lookup -L/Library/Frameworks/R.framework/Resources/lib -L/opt/R/x86_64/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -F/Library/Frameworks/R.framework/.. -framework R
installing to /Library/Frameworks/R.framework/Versions/4.5-x86_64/Resources/library/00LOCK-BufferedMatrix/00new/BufferedMatrix/libs
** R
** inst
** byte-compile and prepare package for lazy loading
Creating a new generic function for ‘rowMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘rowSums’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colSums’ in package ‘BufferedMatrix’
Creating a generic function for ‘ncol’ from package ‘base’ in package ‘BufferedMatrix’
Creating a generic function for ‘nrow’ from package ‘base’ in package ‘BufferedMatrix’
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** checking absolute paths in shared objects and dynamic libraries
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (BufferedMatrix)
BufferedMatrix.Rcheck/tests/c_code_level_tests.Rout
R version 4.5.0 RC (2025-04-04 r88126) -- "How About a Twenty-Six"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix", "BufferedMatrix", .libPaths());.C("dbm_c_tester",integer(1))
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1
Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000
1.000000 2.000000 3.000000 4.000000 5.000000
2.000000 3.000000 4.000000 5.000000 6.000000
3.000000 4.000000 5.000000 6.000000 7.000000
4.000000 5.000000 6.000000 7.000000 8.000000
Adding Additional Column
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
0.000000 1.000000 2.000000 3.000000 4.000000 0.000000
1.000000 2.000000 3.000000 4.000000 5.000000 0.000000
2.000000 3.000000 4.000000 5.000000 6.000000 0.000000
3.000000 4.000000 5.000000 6.000000 7.000000 0.000000
4.000000 5.000000 6.000000 7.000000 8.000000 0.000000
Reassigning values
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 3
Buffer Cols: 3
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Activating Row Buffer
In row mode: 1
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000
Squaring Last Column
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
5.000000 10.000000 15.000000 20.000000 25.000000 900.000000
Square rooting Last Row, then turing off Row Buffer
In row mode: 0
Checking on value that should be not be in column buffer2.236068
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000
2.236068 3.162278 3.872983 4.472136 5.000000 30.000000
Single Indexing. Assign each value its square
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Resizing Buffers Smaller
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000
Activating Row Mode.
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
Activating ReadOnly Mode.
The results of assignment is: 0
Printing matrix reversed.
900.000000 625.000000 400.000000 225.000000 100.000000 25.000000
841.000000 576.000000 361.000000 196.000000 81.000000 16.000000
784.000000 529.000000 324.000000 169.000000 64.000000 9.000000
729.000000 484.000000 289.000000 144.000000 49.000000 -30.000000
676.000000 441.000000 256.000000 121.000000 -20.000000 -10.000000
[[1]]
[1] 0
>
> proc.time()
user system elapsed
0.330 0.154 0.482
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.5.0 RC (2025-04-04 r88126) -- "How About a Twenty-Six"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
>
> ### this is used to control how many repetitions in something below
> ### higher values result in more checks.
> nreps <-100 ##20000
>
>
> ## test creation and some simple assignments and subsetting operations
>
> ## first on single elements
> tmp <- createBufferedMatrix(1000,10)
>
> tmp[10,5]
[1] 0
> tmp[10,5] <- 10
> tmp[10,5]
[1] 10
> tmp[10,5] <- 12.445
> tmp[10,5]
[1] 12.445
>
>
>
> ## now testing accessing multiple elements
> tmp2 <- createBufferedMatrix(10,20)
>
>
> tmp2[3,1] <- 51.34
> tmp2[9,2] <- 9.87654
> tmp2[,1:2]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[,-(3:20)]
[,1] [,2]
[1,] 0.00 0.00000
[2,] 0.00 0.00000
[3,] 51.34 0.00000
[4,] 0.00 0.00000
[5,] 0.00 0.00000
[6,] 0.00 0.00000
[7,] 0.00 0.00000
[8,] 0.00 0.00000
[9,] 0.00 9.87654
[10,] 0.00 0.00000
> tmp2[3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 51.34 0 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
> tmp2[-3,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0 0 0 0 0 0 0
[2,] 0 0 0 0 0 0 0
[3,] 0 0 0 0 0 0 0
[4,] 0 0 0 0 0 0 0
[5,] 0 0 0 0 0 0 0
[6,] 0 0 0 0 0 0 0
[7,] 0 0 0 0 0 0 0
[8,] 0 0 0 0 0 0 0
[9,] 0 0 0 0 0 0 0
> tmp2[2,1:3]
[,1] [,2] [,3]
[1,] 0 0 0
> tmp2[3:9,1:3]
[,1] [,2] [,3]
[1,] 51.34 0.00000 0
[2,] 0.00 0.00000 0
[3,] 0.00 0.00000 0
[4,] 0.00 0.00000 0
[5,] 0.00 0.00000 0
[6,] 0.00 0.00000 0
[7,] 0.00 9.87654 0
> tmp2[-4,-4]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[2,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[3,] 51.34 0.00000 0 0 0 0 0 0 0 0 0 0 0
[4,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[5,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[6,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[7,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[8,] 0.00 9.87654 0 0 0 0 0 0 0 0 0 0 0
[9,] 0.00 0.00000 0 0 0 0 0 0 0 0 0 0 0
[,14] [,15] [,16] [,17] [,18] [,19]
[1,] 0 0 0 0 0 0
[2,] 0 0 0 0 0 0
[3,] 0 0 0 0 0 0
[4,] 0 0 0 0 0 0
[5,] 0 0 0 0 0 0
[6,] 0 0 0 0 0 0
[7,] 0 0 0 0 0 0
[8,] 0 0 0 0 0 0
[9,] 0 0 0 0 0 0
>
> ## now testing accessing/assigning multiple elements
> tmp3 <- createBufferedMatrix(10,10)
>
> for (i in 1:10){
+ for (j in 1:10){
+ tmp3[i,j] <- (j-1)*10 + i
+ }
+ }
>
> tmp3[2:4,2:4]
[,1] [,2] [,3]
[1,] 12 22 32
[2,] 13 23 33
[3,] 14 24 34
> tmp3[c(-10),c(2:4,2:4,10,1,2,1:10,10:1)]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 11 21 31 11 21 31 91 1 11 1 11 21 31
[2,] 12 22 32 12 22 32 92 2 12 2 12 22 32
[3,] 13 23 33 13 23 33 93 3 13 3 13 23 33
[4,] 14 24 34 14 24 34 94 4 14 4 14 24 34
[5,] 15 25 35 15 25 35 95 5 15 5 15 25 35
[6,] 16 26 36 16 26 36 96 6 16 6 16 26 36
[7,] 17 27 37 17 27 37 97 7 17 7 17 27 37
[8,] 18 28 38 18 28 38 98 8 18 8 18 28 38
[9,] 19 29 39 19 29 39 99 9 19 9 19 29 39
[,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25]
[1,] 41 51 61 71 81 91 91 81 71 61 51 41
[2,] 42 52 62 72 82 92 92 82 72 62 52 42
[3,] 43 53 63 73 83 93 93 83 73 63 53 43
[4,] 44 54 64 74 84 94 94 84 74 64 54 44
[5,] 45 55 65 75 85 95 95 85 75 65 55 45
[6,] 46 56 66 76 86 96 96 86 76 66 56 46
[7,] 47 57 67 77 87 97 97 87 77 67 57 47
[8,] 48 58 68 78 88 98 98 88 78 68 58 48
[9,] 49 59 69 79 89 99 99 89 79 69 59 49
[,26] [,27] [,28] [,29]
[1,] 31 21 11 1
[2,] 32 22 12 2
[3,] 33 23 13 3
[4,] 34 24 14 4
[5,] 35 25 15 5
[6,] 36 26 16 6
[7,] 37 27 17 7
[8,] 38 28 18 8
[9,] 39 29 19 9
> tmp3[-c(1:5),-c(6:10)]
[,1] [,2] [,3] [,4] [,5]
[1,] 6 16 26 36 46
[2,] 7 17 27 37 47
[3,] 8 18 28 38 48
[4,] 9 19 29 39 49
[5,] 10 20 30 40 50
>
> ## assignment of whole columns
> tmp3[,1] <- c(1:10*100.0)
> tmp3[,1:2] <- tmp3[,1:2]*100
> tmp3[,1:2] <- tmp3[,2:1]
> tmp3[,1:2]
[,1] [,2]
[1,] 1100 1e+04
[2,] 1200 2e+04
[3,] 1300 3e+04
[4,] 1400 4e+04
[5,] 1500 5e+04
[6,] 1600 6e+04
[7,] 1700 7e+04
[8,] 1800 8e+04
[9,] 1900 9e+04
[10,] 2000 1e+05
>
>
> tmp3[,-1] <- tmp3[,1:9]
> tmp3[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1100 1100 1e+04 21 31 41 51 61 71 81
[2,] 1200 1200 2e+04 22 32 42 52 62 72 82
[3,] 1300 1300 3e+04 23 33 43 53 63 73 83
[4,] 1400 1400 4e+04 24 34 44 54 64 74 84
[5,] 1500 1500 5e+04 25 35 45 55 65 75 85
[6,] 1600 1600 6e+04 26 36 46 56 66 76 86
[7,] 1700 1700 7e+04 27 37 47 57 67 77 87
[8,] 1800 1800 8e+04 28 38 48 58 68 78 88
[9,] 1900 1900 9e+04 29 39 49 59 69 79 89
[10,] 2000 2000 1e+05 30 40 50 60 70 80 90
>
> tmp3[,1:2] <- rep(1,10)
> tmp3[,1:2] <- rep(1,20)
> tmp3[,1:2] <- matrix(c(1:5),1,5)
>
> tmp3[,-c(1:8)] <- matrix(c(1:5),1,5)
>
> tmp3[1,] <- 1:10
> tmp3[1,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
> tmp3[-1,] <- c(1,2)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 2 1 2 1 2 1 2 1 2 1
[10,] 1 2 1 2 1 2 1 2 1 2
> tmp3[-c(1:8),] <- matrix(c(1:5),1,5)
> tmp3[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 2 3 4 5 6 7 8 9 10
[2,] 1 2 1 2 1 2 1 2 1 2
[3,] 2 1 2 1 2 1 2 1 2 1
[4,] 1 2 1 2 1 2 1 2 1 2
[5,] 2 1 2 1 2 1 2 1 2 1
[6,] 1 2 1 2 1 2 1 2 1 2
[7,] 2 1 2 1 2 1 2 1 2 1
[8,] 1 2 1 2 1 2 1 2 1 2
[9,] 1 3 5 2 4 1 3 5 2 4
[10,] 2 4 1 3 5 2 4 1 3 5
>
>
> tmp3[1:2,1:2] <- 5555.04
> tmp3[-(1:2),1:2] <- 1234.56789
>
>
>
> ## testing accessors for the directory and prefix
> directory(tmp3)
[1] "/Users/biocbuild/bbs-3.21-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 480829 25.7 1056567 56.5 NA 634460 33.9
Vcells 891038 6.8 8388608 64.0 98304 2108474 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] "Mon Apr 21 19:30:19 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] "Mon Apr 21 19:30:19 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: 0x600003b1c000>
>
>
>
> 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] "Mon Apr 21 19:30:24 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] "Mon Apr 21 19:30:26 2025"
>
> ColMode(tmp2)
<pointer: 0x600003b1c000>
>
>
>
> ### 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,] 100.08087719 -1.3835122 -0.04950337 1.4688777
[2,] -0.01224922 -1.6478223 1.27929802 -1.5457689
[3,] 0.33296817 -0.7979778 0.61103914 1.2232708
[4,] -1.44635544 1.4481235 -1.25102016 -0.6827258
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.21-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,] 100.08087719 1.3835122 0.04950337 1.4688777
[2,] 0.01224922 1.6478223 1.27929802 1.5457689
[3,] 0.33296817 0.7979778 0.61103914 1.2232708
[4,] 1.44635544 1.4481235 1.25102016 0.6827258
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.21-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,] 10.0040430 1.1762280 0.2224935 1.2119727
[2,] 0.1106762 1.2836753 1.1310606 1.2432896
[3,] 0.5770339 0.8932961 0.7816899 1.1060157
[4,] 1.2026452 1.2033800 1.1184901 0.8262722
>
> 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-3.21-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,] 225.12131 38.14579 27.27444 38.58860
[2,] 26.11901 39.48458 37.58990 38.97866
[3,] 31.10331 34.73094 33.42794 37.28343
[4,] 38.47281 38.48192 37.43592 33.94545
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x600003b60000>
> exp(tmp5)
<pointer: 0x600003b60000>
> log(tmp5,2)
<pointer: 0x600003b60000>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 468.5605
> Min(tmp5)
[1] 52.67917
> mean(tmp5)
[1] 72.99484
> Sum(tmp5)
[1] 14598.97
> Var(tmp5)
[1] 872.8917
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 89.95961 69.66418 71.34999 73.99226 71.45676 69.90432 71.00471 68.53406
[9] 70.50941 73.57316
> rowSums(tmp5)
[1] 1799.192 1393.284 1427.000 1479.845 1429.135 1398.086 1420.094 1370.681
[9] 1410.188 1471.463
> rowVars(tmp5)
[1] 8042.19086 59.95277 82.36703 66.08858 73.31685 99.84962
[7] 88.41446 79.04602 70.71474 117.41447
> rowSd(tmp5)
[1] 89.678263 7.742918 9.075628 8.129488 8.562526 9.992478 9.402896
[8] 8.890783 8.409206 10.835796
> rowMax(tmp5)
[1] 468.56051 82.18197 88.50759 89.71621 84.58862 87.94220 88.43842
[8] 85.17829 85.19492 89.78343
> rowMin(tmp5)
[1] 54.70905 54.36330 55.18859 57.32865 52.67917 53.12837 58.59815 54.82914
[9] 58.39016 54.90789
>
> colMeans(tmp5)
[1] 109.68850 74.89383 72.19480 78.13745 70.65523 74.60554 71.50646
[8] 71.26525 65.66568 66.64391 71.51782 72.52536 69.39031 70.94044
[15] 66.62252 69.95099 72.83536 69.15454 71.41132 70.29160
> colSums(tmp5)
[1] 1096.8850 748.9383 721.9480 781.3745 706.5523 746.0554 715.0646
[8] 712.6525 656.6568 666.4391 715.1782 725.2536 693.9031 709.4044
[15] 666.2252 699.5099 728.3536 691.5454 714.1132 702.9160
> colVars(tmp5)
[1] 15978.02471 71.44348 82.26244 52.53688 107.03898 95.33851
[7] 104.58998 97.83930 94.86087 74.10241 85.57036 18.42149
[13] 37.67589 95.52324 70.18642 128.55741 113.26158 96.45299
[19] 91.52684 51.48302
> colSd(tmp5)
[1] 126.404212 8.452424 9.069865 7.248233 10.345964 9.764144
[7] 10.226924 9.891375 9.739654 8.608276 9.250425 4.292027
[13] 6.138069 9.773599 8.377733 11.338316 10.642442 9.821048
[19] 9.566966 7.175167
> colMax(tmp5)
[1] 468.56051 87.47993 89.29262 87.94220 89.71621 89.78343 84.68181
[8] 85.11784 85.01851 81.97348 82.81813 78.20405 79.73808 84.58862
[15] 80.95937 85.17829 88.50759 88.43842 85.88881 80.00369
> colMin(tmp5)
[1] 54.36330 64.23588 56.76817 63.15245 55.18859 56.28584 56.43041 59.64114
[9] 54.70905 52.67917 55.50774 64.62922 57.24196 54.82914 57.38161 53.12837
[17] 57.40461 56.38474 60.41958 57.18487
>
>
> ### 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] 89.95961 69.66418 71.34999 NA 71.45676 69.90432 71.00471 68.53406
[9] 70.50941 73.57316
> rowSums(tmp5)
[1] 1799.192 1393.284 1427.000 NA 1429.135 1398.086 1420.094 1370.681
[9] 1410.188 1471.463
> rowVars(tmp5)
[1] 8042.19086 59.95277 82.36703 68.55738 73.31685 99.84962
[7] 88.41446 79.04602 70.71474 117.41447
> rowSd(tmp5)
[1] 89.678263 7.742918 9.075628 8.279938 8.562526 9.992478 9.402896
[8] 8.890783 8.409206 10.835796
> rowMax(tmp5)
[1] 468.56051 82.18197 88.50759 NA 84.58862 87.94220 88.43842
[8] 85.17829 85.19492 89.78343
> rowMin(tmp5)
[1] 54.70905 54.36330 55.18859 NA 52.67917 53.12837 58.59815 54.82914
[9] 58.39016 54.90789
>
> colMeans(tmp5)
[1] 109.68850 74.89383 72.19480 78.13745 70.65523 74.60554 71.50646
[8] 71.26525 65.66568 66.64391 71.51782 NA 69.39031 70.94044
[15] 66.62252 69.95099 72.83536 69.15454 71.41132 70.29160
> colSums(tmp5)
[1] 1096.8850 748.9383 721.9480 781.3745 706.5523 746.0554 715.0646
[8] 712.6525 656.6568 666.4391 715.1782 NA 693.9031 709.4044
[15] 666.2252 699.5099 728.3536 691.5454 714.1132 702.9160
> colVars(tmp5)
[1] 15978.02471 71.44348 82.26244 52.53688 107.03898 95.33851
[7] 104.58998 97.83930 94.86087 74.10241 85.57036 NA
[13] 37.67589 95.52324 70.18642 128.55741 113.26158 96.45299
[19] 91.52684 51.48302
> colSd(tmp5)
[1] 126.404212 8.452424 9.069865 7.248233 10.345964 9.764144
[7] 10.226924 9.891375 9.739654 8.608276 9.250425 NA
[13] 6.138069 9.773599 8.377733 11.338316 10.642442 9.821048
[19] 9.566966 7.175167
> colMax(tmp5)
[1] 468.56051 87.47993 89.29262 87.94220 89.71621 89.78343 84.68181
[8] 85.11784 85.01851 81.97348 82.81813 NA 79.73808 84.58862
[15] 80.95937 85.17829 88.50759 88.43842 85.88881 80.00369
> colMin(tmp5)
[1] 54.36330 64.23588 56.76817 63.15245 55.18859 56.28584 56.43041 59.64114
[9] 54.70905 52.67917 55.50774 NA 57.24196 54.82914 57.38161 53.12837
[17] 57.40461 56.38474 60.41958 57.18487
>
> Max(tmp5,na.rm=TRUE)
[1] 468.5605
> Min(tmp5,na.rm=TRUE)
[1] 52.67917
> mean(tmp5,na.rm=TRUE)
[1] 73.01262
> Sum(tmp5,na.rm=TRUE)
[1] 14529.51
> Var(tmp5,na.rm=TRUE)
[1] 877.2367
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 89.95961 69.66418 71.34999 74.23095 71.45676 69.90432 71.00471 68.53406
[9] 70.50941 73.57316
> rowSums(tmp5,na.rm=TRUE)
[1] 1799.192 1393.284 1427.000 1410.388 1429.135 1398.086 1420.094 1370.681
[9] 1410.188 1471.463
> rowVars(tmp5,na.rm=TRUE)
[1] 8042.19086 59.95277 82.36703 68.55738 73.31685 99.84962
[7] 88.41446 79.04602 70.71474 117.41447
> rowSd(tmp5,na.rm=TRUE)
[1] 89.678263 7.742918 9.075628 8.279938 8.562526 9.992478 9.402896
[8] 8.890783 8.409206 10.835796
> rowMax(tmp5,na.rm=TRUE)
[1] 468.56051 82.18197 88.50759 89.71621 84.58862 87.94220 88.43842
[8] 85.17829 85.19492 89.78343
> rowMin(tmp5,na.rm=TRUE)
[1] 54.70905 54.36330 55.18859 57.32865 52.67917 53.12837 58.59815 54.82914
[9] 58.39016 54.90789
>
> colMeans(tmp5,na.rm=TRUE)
[1] 109.68850 74.89383 72.19480 78.13745 70.65523 74.60554 71.50646
[8] 71.26525 65.66568 66.64391 71.51782 72.86628 69.39031 70.94044
[15] 66.62252 69.95099 72.83536 69.15454 71.41132 70.29160
> colSums(tmp5,na.rm=TRUE)
[1] 1096.8850 748.9383 721.9480 781.3745 706.5523 746.0554 715.0646
[8] 712.6525 656.6568 666.4391 715.1782 655.7965 693.9031 709.4044
[15] 666.2252 699.5099 728.3536 691.5454 714.1132 702.9160
> colVars(tmp5,na.rm=TRUE)
[1] 15978.02471 71.44348 82.26244 52.53688 107.03898 95.33851
[7] 104.58998 97.83930 94.86087 74.10241 85.57036 19.41664
[13] 37.67589 95.52324 70.18642 128.55741 113.26158 96.45299
[19] 91.52684 51.48302
> colSd(tmp5,na.rm=TRUE)
[1] 126.404212 8.452424 9.069865 7.248233 10.345964 9.764144
[7] 10.226924 9.891375 9.739654 8.608276 9.250425 4.406432
[13] 6.138069 9.773599 8.377733 11.338316 10.642442 9.821048
[19] 9.566966 7.175167
> colMax(tmp5,na.rm=TRUE)
[1] 468.56051 87.47993 89.29262 87.94220 89.71621 89.78343 84.68181
[8] 85.11784 85.01851 81.97348 82.81813 78.20405 79.73808 84.58862
[15] 80.95937 85.17829 88.50759 88.43842 85.88881 80.00369
> colMin(tmp5,na.rm=TRUE)
[1] 54.36330 64.23588 56.76817 63.15245 55.18859 56.28584 56.43041 59.64114
[9] 54.70905 52.67917 55.50774 64.62922 57.24196 54.82914 57.38161 53.12837
[17] 57.40461 56.38474 60.41958 57.18487
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 89.95961 69.66418 71.34999 NaN 71.45676 69.90432 71.00471 68.53406
[9] 70.50941 73.57316
> rowSums(tmp5,na.rm=TRUE)
[1] 1799.192 1393.284 1427.000 0.000 1429.135 1398.086 1420.094 1370.681
[9] 1410.188 1471.463
> rowVars(tmp5,na.rm=TRUE)
[1] 8042.19086 59.95277 82.36703 NA 73.31685 99.84962
[7] 88.41446 79.04602 70.71474 117.41447
> rowSd(tmp5,na.rm=TRUE)
[1] 89.678263 7.742918 9.075628 NA 8.562526 9.992478 9.402896
[8] 8.890783 8.409206 10.835796
> rowMax(tmp5,na.rm=TRUE)
[1] 468.56051 82.18197 88.50759 NA 84.58862 87.94220 88.43842
[8] 85.17829 85.19492 89.78343
> rowMin(tmp5,na.rm=TRUE)
[1] 54.70905 54.36330 55.18859 NA 52.67917 53.12837 58.59815 54.82914
[9] 58.39016 54.90789
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 112.97876 74.31591 71.55889 78.96906 68.53734 74.69756 71.12853
[8] 71.43518 64.68064 66.69065 70.63719 NaN 69.01664 69.69331
[15] 66.72169 69.07933 74.54989 70.46852 70.44258 69.21248
> colSums(tmp5,na.rm=TRUE)
[1] 1016.8089 668.8432 644.0300 710.7215 616.8361 672.2780 640.1568
[8] 642.9166 582.1258 600.2158 635.7347 0.0000 621.1498 627.2398
[15] 600.4952 621.7140 670.9490 634.2167 633.9833 622.9123
> colVars(tmp5,na.rm=TRUE)
[1] 17853.48701 76.61654 87.99599 51.32386 69.95760 107.16056
[7] 116.05685 109.74436 95.80251 83.34064 87.54222 NA
[13] 40.81451 89.96620 78.84908 136.07947 94.34871 89.08579
[19] 92.41017 44.81773
> colSd(tmp5,na.rm=TRUE)
[1] 133.616941 8.753088 9.380618 7.164067 8.364066 10.351838
[7] 10.772968 10.475894 9.787876 9.129109 9.356400 NA
[13] 6.388623 9.485051 8.879701 11.665311 9.713326 9.438527
[19] 9.613021 6.694604
> colMax(tmp5,na.rm=TRUE)
[1] 468.56051 87.47993 89.29262 87.94220 84.33356 89.78343 84.68181
[8] 85.11784 85.01851 81.97348 82.81813 -Inf 79.73808 84.58862
[15] 80.95937 85.17829 88.50759 88.43842 85.88881 79.70022
> colMin(tmp5,na.rm=TRUE)
[1] 54.36330 64.23588 56.76817 63.15245 55.18859 56.28584 56.43041 59.64114
[9] 54.70905 52.67917 55.50774 Inf 57.24196 54.82914 57.38161 53.12837
[17] 62.96043 56.38474 60.41958 57.18487
>
>
>
>
> 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] 182.2734 262.9593 198.3232 213.3127 268.2402 184.5618 152.9799 158.4565
[9] 215.8732 178.1371
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 182.2734 262.9593 198.3232 213.3127 268.2402 184.5618 152.9799 158.4565
[9] 215.8732 178.1371
>
>
>
> 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] 1.136868e-13 1.136868e-13 1.136868e-13 -2.842171e-14 -1.705303e-13
[6] 1.136868e-13 2.842171e-14 -8.526513e-14 2.842171e-14 5.684342e-14
[11] 1.705303e-13 -2.842171e-13 1.136868e-13 1.136868e-13 -3.410605e-13
[16] -1.705303e-13 -8.526513e-14 0.000000e+00 1.136868e-13 5.684342e-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)
+ }
9 4
6 15
5 12
1 10
10 5
2 18
9 12
5 7
1 11
9 12
10 12
4 12
5 20
1 19
6 3
4 7
2 14
10 11
2 20
8 7
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] 2.907621
> Min(tmp)
[1] -2.466331
> mean(tmp)
[1] 0.03391174
> Sum(tmp)
[1] 3.391174
> Var(tmp)
[1] 1.001403
>
> rowMeans(tmp)
[1] 0.03391174
> rowSums(tmp)
[1] 3.391174
> rowVars(tmp)
[1] 1.001403
> rowSd(tmp)
[1] 1.000701
> rowMax(tmp)
[1] 2.907621
> rowMin(tmp)
[1] -2.466331
>
> colMeans(tmp)
[1] 0.1982970542 2.9076209052 -0.5762875604 -0.1872004330 -1.4889626817
[6] 1.1899194753 0.7045495460 -1.2253938017 0.7680511080 1.3841146111
[11] 0.8784925984 -0.7127252635 0.0408402422 0.3859297811 1.0064965041
[16] -1.0292228805 1.5005863117 -0.6679732618 -1.2223588870 0.7861584770
[21] 1.3746080707 -0.9024760848 0.0449556760 -1.2255534108 0.5896026212
[26] 0.6200610469 0.4406273174 -0.7463790262 2.1526276574 0.8474577835
[31] -0.0459066679 0.2623459344 0.4489379982 -0.3022357003 -0.1877076757
[36] -1.1475460904 -0.0677931191 -1.2611008822 -0.8449530976 0.0004995457
[41] -0.3494630774 0.9204166477 0.0437914557 -1.1667360870 -1.0236098818
[46] -0.1305069418 0.8754922176 -0.9912851440 -1.2410039359 0.6517782253
[51] 0.6111571617 -0.8614418692 -0.7788511556 0.6359205701 0.0921420173
[56] 1.5266790035 -0.3158742628 1.9425565788 0.3885399742 -0.9633732591
[61] -0.9988696185 0.9162807773 -1.3116302123 0.0085045604 0.9073070986
[66] -0.4117469301 -0.2576114335 1.0409042361 -0.1285904206 -2.1752125673
[71] 0.0371336806 -2.4663309354 0.4751861208 -0.8838510556 -0.0938132285
[76] 0.5831425168 -2.2752648660 -0.0409961462 1.7606755038 1.0816705818
[81] -0.4109341824 0.7436142498 0.1586141375 -0.4658242778 0.2855966588
[86] 0.5802649176 0.3629491259 0.9535606162 -0.5510056390 1.6889781084
[91] 1.0264138382 -0.5945910290 0.2085753110 1.7612881922 0.1709703595
[96] -1.4645310883 -0.0382595045 -0.4569668033 -1.4693212968 0.5775623819
> colSums(tmp)
[1] 0.1982970542 2.9076209052 -0.5762875604 -0.1872004330 -1.4889626817
[6] 1.1899194753 0.7045495460 -1.2253938017 0.7680511080 1.3841146111
[11] 0.8784925984 -0.7127252635 0.0408402422 0.3859297811 1.0064965041
[16] -1.0292228805 1.5005863117 -0.6679732618 -1.2223588870 0.7861584770
[21] 1.3746080707 -0.9024760848 0.0449556760 -1.2255534108 0.5896026212
[26] 0.6200610469 0.4406273174 -0.7463790262 2.1526276574 0.8474577835
[31] -0.0459066679 0.2623459344 0.4489379982 -0.3022357003 -0.1877076757
[36] -1.1475460904 -0.0677931191 -1.2611008822 -0.8449530976 0.0004995457
[41] -0.3494630774 0.9204166477 0.0437914557 -1.1667360870 -1.0236098818
[46] -0.1305069418 0.8754922176 -0.9912851440 -1.2410039359 0.6517782253
[51] 0.6111571617 -0.8614418692 -0.7788511556 0.6359205701 0.0921420173
[56] 1.5266790035 -0.3158742628 1.9425565788 0.3885399742 -0.9633732591
[61] -0.9988696185 0.9162807773 -1.3116302123 0.0085045604 0.9073070986
[66] -0.4117469301 -0.2576114335 1.0409042361 -0.1285904206 -2.1752125673
[71] 0.0371336806 -2.4663309354 0.4751861208 -0.8838510556 -0.0938132285
[76] 0.5831425168 -2.2752648660 -0.0409961462 1.7606755038 1.0816705818
[81] -0.4109341824 0.7436142498 0.1586141375 -0.4658242778 0.2855966588
[86] 0.5802649176 0.3629491259 0.9535606162 -0.5510056390 1.6889781084
[91] 1.0264138382 -0.5945910290 0.2085753110 1.7612881922 0.1709703595
[96] -1.4645310883 -0.0382595045 -0.4569668033 -1.4693212968 0.5775623819
> 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] 0.1982970542 2.9076209052 -0.5762875604 -0.1872004330 -1.4889626817
[6] 1.1899194753 0.7045495460 -1.2253938017 0.7680511080 1.3841146111
[11] 0.8784925984 -0.7127252635 0.0408402422 0.3859297811 1.0064965041
[16] -1.0292228805 1.5005863117 -0.6679732618 -1.2223588870 0.7861584770
[21] 1.3746080707 -0.9024760848 0.0449556760 -1.2255534108 0.5896026212
[26] 0.6200610469 0.4406273174 -0.7463790262 2.1526276574 0.8474577835
[31] -0.0459066679 0.2623459344 0.4489379982 -0.3022357003 -0.1877076757
[36] -1.1475460904 -0.0677931191 -1.2611008822 -0.8449530976 0.0004995457
[41] -0.3494630774 0.9204166477 0.0437914557 -1.1667360870 -1.0236098818
[46] -0.1305069418 0.8754922176 -0.9912851440 -1.2410039359 0.6517782253
[51] 0.6111571617 -0.8614418692 -0.7788511556 0.6359205701 0.0921420173
[56] 1.5266790035 -0.3158742628 1.9425565788 0.3885399742 -0.9633732591
[61] -0.9988696185 0.9162807773 -1.3116302123 0.0085045604 0.9073070986
[66] -0.4117469301 -0.2576114335 1.0409042361 -0.1285904206 -2.1752125673
[71] 0.0371336806 -2.4663309354 0.4751861208 -0.8838510556 -0.0938132285
[76] 0.5831425168 -2.2752648660 -0.0409961462 1.7606755038 1.0816705818
[81] -0.4109341824 0.7436142498 0.1586141375 -0.4658242778 0.2855966588
[86] 0.5802649176 0.3629491259 0.9535606162 -0.5510056390 1.6889781084
[91] 1.0264138382 -0.5945910290 0.2085753110 1.7612881922 0.1709703595
[96] -1.4645310883 -0.0382595045 -0.4569668033 -1.4693212968 0.5775623819
> colMin(tmp)
[1] 0.1982970542 2.9076209052 -0.5762875604 -0.1872004330 -1.4889626817
[6] 1.1899194753 0.7045495460 -1.2253938017 0.7680511080 1.3841146111
[11] 0.8784925984 -0.7127252635 0.0408402422 0.3859297811 1.0064965041
[16] -1.0292228805 1.5005863117 -0.6679732618 -1.2223588870 0.7861584770
[21] 1.3746080707 -0.9024760848 0.0449556760 -1.2255534108 0.5896026212
[26] 0.6200610469 0.4406273174 -0.7463790262 2.1526276574 0.8474577835
[31] -0.0459066679 0.2623459344 0.4489379982 -0.3022357003 -0.1877076757
[36] -1.1475460904 -0.0677931191 -1.2611008822 -0.8449530976 0.0004995457
[41] -0.3494630774 0.9204166477 0.0437914557 -1.1667360870 -1.0236098818
[46] -0.1305069418 0.8754922176 -0.9912851440 -1.2410039359 0.6517782253
[51] 0.6111571617 -0.8614418692 -0.7788511556 0.6359205701 0.0921420173
[56] 1.5266790035 -0.3158742628 1.9425565788 0.3885399742 -0.9633732591
[61] -0.9988696185 0.9162807773 -1.3116302123 0.0085045604 0.9073070986
[66] -0.4117469301 -0.2576114335 1.0409042361 -0.1285904206 -2.1752125673
[71] 0.0371336806 -2.4663309354 0.4751861208 -0.8838510556 -0.0938132285
[76] 0.5831425168 -2.2752648660 -0.0409961462 1.7606755038 1.0816705818
[81] -0.4109341824 0.7436142498 0.1586141375 -0.4658242778 0.2855966588
[86] 0.5802649176 0.3629491259 0.9535606162 -0.5510056390 1.6889781084
[91] 1.0264138382 -0.5945910290 0.2085753110 1.7612881922 0.1709703595
[96] -1.4645310883 -0.0382595045 -0.4569668033 -1.4693212968 0.5775623819
> colMedians(tmp)
[1] 0.1982970542 2.9076209052 -0.5762875604 -0.1872004330 -1.4889626817
[6] 1.1899194753 0.7045495460 -1.2253938017 0.7680511080 1.3841146111
[11] 0.8784925984 -0.7127252635 0.0408402422 0.3859297811 1.0064965041
[16] -1.0292228805 1.5005863117 -0.6679732618 -1.2223588870 0.7861584770
[21] 1.3746080707 -0.9024760848 0.0449556760 -1.2255534108 0.5896026212
[26] 0.6200610469 0.4406273174 -0.7463790262 2.1526276574 0.8474577835
[31] -0.0459066679 0.2623459344 0.4489379982 -0.3022357003 -0.1877076757
[36] -1.1475460904 -0.0677931191 -1.2611008822 -0.8449530976 0.0004995457
[41] -0.3494630774 0.9204166477 0.0437914557 -1.1667360870 -1.0236098818
[46] -0.1305069418 0.8754922176 -0.9912851440 -1.2410039359 0.6517782253
[51] 0.6111571617 -0.8614418692 -0.7788511556 0.6359205701 0.0921420173
[56] 1.5266790035 -0.3158742628 1.9425565788 0.3885399742 -0.9633732591
[61] -0.9988696185 0.9162807773 -1.3116302123 0.0085045604 0.9073070986
[66] -0.4117469301 -0.2576114335 1.0409042361 -0.1285904206 -2.1752125673
[71] 0.0371336806 -2.4663309354 0.4751861208 -0.8838510556 -0.0938132285
[76] 0.5831425168 -2.2752648660 -0.0409961462 1.7606755038 1.0816705818
[81] -0.4109341824 0.7436142498 0.1586141375 -0.4658242778 0.2855966588
[86] 0.5802649176 0.3629491259 0.9535606162 -0.5510056390 1.6889781084
[91] 1.0264138382 -0.5945910290 0.2085753110 1.7612881922 0.1709703595
[96] -1.4645310883 -0.0382595045 -0.4569668033 -1.4693212968 0.5775623819
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.1982971 2.907621 -0.5762876 -0.1872004 -1.488963 1.189919 0.7045495
[2,] 0.1982971 2.907621 -0.5762876 -0.1872004 -1.488963 1.189919 0.7045495
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -1.225394 0.7680511 1.384115 0.8784926 -0.7127253 0.04084024 0.3859298
[2,] -1.225394 0.7680511 1.384115 0.8784926 -0.7127253 0.04084024 0.3859298
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 1.006497 -1.029223 1.500586 -0.6679733 -1.222359 0.7861585 1.374608
[2,] 1.006497 -1.029223 1.500586 -0.6679733 -1.222359 0.7861585 1.374608
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] -0.9024761 0.04495568 -1.225553 0.5896026 0.620061 0.4406273 -0.746379
[2,] -0.9024761 0.04495568 -1.225553 0.5896026 0.620061 0.4406273 -0.746379
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 2.152628 0.8474578 -0.04590667 0.2623459 0.448938 -0.3022357 -0.1877077
[2,] 2.152628 0.8474578 -0.04590667 0.2623459 0.448938 -0.3022357 -0.1877077
[,36] [,37] [,38] [,39] [,40] [,41]
[1,] -1.147546 -0.06779312 -1.261101 -0.8449531 0.0004995457 -0.3494631
[2,] -1.147546 -0.06779312 -1.261101 -0.8449531 0.0004995457 -0.3494631
[,42] [,43] [,44] [,45] [,46] [,47] [,48]
[1,] 0.9204166 0.04379146 -1.166736 -1.02361 -0.1305069 0.8754922 -0.9912851
[2,] 0.9204166 0.04379146 -1.166736 -1.02361 -0.1305069 0.8754922 -0.9912851
[,49] [,50] [,51] [,52] [,53] [,54] [,55]
[1,] -1.241004 0.6517782 0.6111572 -0.8614419 -0.7788512 0.6359206 0.09214202
[2,] -1.241004 0.6517782 0.6111572 -0.8614419 -0.7788512 0.6359206 0.09214202
[,56] [,57] [,58] [,59] [,60] [,61] [,62]
[1,] 1.526679 -0.3158743 1.942557 0.38854 -0.9633733 -0.9988696 0.9162808
[2,] 1.526679 -0.3158743 1.942557 0.38854 -0.9633733 -0.9988696 0.9162808
[,63] [,64] [,65] [,66] [,67] [,68] [,69]
[1,] -1.31163 0.00850456 0.9073071 -0.4117469 -0.2576114 1.040904 -0.1285904
[2,] -1.31163 0.00850456 0.9073071 -0.4117469 -0.2576114 1.040904 -0.1285904
[,70] [,71] [,72] [,73] [,74] [,75] [,76]
[1,] -2.175213 0.03713368 -2.466331 0.4751861 -0.8838511 -0.09381323 0.5831425
[2,] -2.175213 0.03713368 -2.466331 0.4751861 -0.8838511 -0.09381323 0.5831425
[,77] [,78] [,79] [,80] [,81] [,82] [,83]
[1,] -2.275265 -0.04099615 1.760676 1.081671 -0.4109342 0.7436142 0.1586141
[2,] -2.275265 -0.04099615 1.760676 1.081671 -0.4109342 0.7436142 0.1586141
[,84] [,85] [,86] [,87] [,88] [,89] [,90]
[1,] -0.4658243 0.2855967 0.5802649 0.3629491 0.9535606 -0.5510056 1.688978
[2,] -0.4658243 0.2855967 0.5802649 0.3629491 0.9535606 -0.5510056 1.688978
[,91] [,92] [,93] [,94] [,95] [,96] [,97]
[1,] 1.026414 -0.594591 0.2085753 1.761288 0.1709704 -1.464531 -0.0382595
[2,] 1.026414 -0.594591 0.2085753 1.761288 0.1709704 -1.464531 -0.0382595
[,98] [,99] [,100]
[1,] -0.4569668 -1.469321 0.5775624
[2,] -0.4569668 -1.469321 0.5775624
>
>
> Max(tmp2)
[1] 2.826684
> Min(tmp2)
[1] -2.121732
> mean(tmp2)
[1] 0.1408192
> Sum(tmp2)
[1] 14.08192
> Var(tmp2)
[1] 1.082989
>
> rowMeans(tmp2)
[1] 0.7976614449 -1.2575368953 0.2334617144 -0.5390310938 -0.3032363193
[6] -0.1251638340 1.2920972872 0.4426417110 -0.3204030282 0.6208987936
[11] 0.9528292793 1.2195944700 -0.7536693822 1.6741329212 0.0514828239
[16] -1.3104392298 -1.1353261740 -0.7781482774 -0.4319665172 1.0002697768
[21] 0.6504770483 1.5290070477 -0.9160970763 -0.9411092813 1.4185913621
[26] 0.1570323145 0.9828201286 1.1619904388 0.5231244093 -0.4973783370
[31] -0.0002813796 -1.8197856389 -1.6479691975 -0.3283955108 -0.7233960555
[36] -2.0261919053 2.8266842406 -0.4234423550 -1.0413722342 -1.0313668971
[41] 0.5813499456 -0.5672738901 1.1034697951 -0.2273929450 1.3043246048
[46] 0.3448917809 0.8414990485 1.6232117136 -1.6322234262 -0.3334772950
[51] -0.6702078756 -0.1298583196 0.1728347137 0.2391782739 -0.0948429116
[56] 1.4629522319 1.3543415934 0.2654116345 -0.6439977221 2.3890608444
[61] 0.4343796525 0.6336823705 -0.0942712632 -0.1329281034 2.0322354883
[66] -0.5540766541 1.1144670597 -1.6880750574 -1.0406707663 0.5170928254
[71] -0.1821217394 0.8460626106 0.6500223498 0.8978831906 -0.4550459878
[76] -0.6888255265 0.6643134895 -1.2927318811 0.2077209663 -0.7589686896
[81] 2.1100254701 0.5697765734 -0.4557291637 0.5030609848 -0.5365588207
[86] 2.5302508073 0.1654886594 -1.2576489132 0.7056407279 0.4729848845
[91] -2.1217322670 -1.0410798386 0.1338956520 1.2225372627 1.6905431172
[96] 0.1739593419 0.6789511418 1.3417585203 -0.0666142353 -0.4140724400
> rowSums(tmp2)
[1] 0.7976614449 -1.2575368953 0.2334617144 -0.5390310938 -0.3032363193
[6] -0.1251638340 1.2920972872 0.4426417110 -0.3204030282 0.6208987936
[11] 0.9528292793 1.2195944700 -0.7536693822 1.6741329212 0.0514828239
[16] -1.3104392298 -1.1353261740 -0.7781482774 -0.4319665172 1.0002697768
[21] 0.6504770483 1.5290070477 -0.9160970763 -0.9411092813 1.4185913621
[26] 0.1570323145 0.9828201286 1.1619904388 0.5231244093 -0.4973783370
[31] -0.0002813796 -1.8197856389 -1.6479691975 -0.3283955108 -0.7233960555
[36] -2.0261919053 2.8266842406 -0.4234423550 -1.0413722342 -1.0313668971
[41] 0.5813499456 -0.5672738901 1.1034697951 -0.2273929450 1.3043246048
[46] 0.3448917809 0.8414990485 1.6232117136 -1.6322234262 -0.3334772950
[51] -0.6702078756 -0.1298583196 0.1728347137 0.2391782739 -0.0948429116
[56] 1.4629522319 1.3543415934 0.2654116345 -0.6439977221 2.3890608444
[61] 0.4343796525 0.6336823705 -0.0942712632 -0.1329281034 2.0322354883
[66] -0.5540766541 1.1144670597 -1.6880750574 -1.0406707663 0.5170928254
[71] -0.1821217394 0.8460626106 0.6500223498 0.8978831906 -0.4550459878
[76] -0.6888255265 0.6643134895 -1.2927318811 0.2077209663 -0.7589686896
[81] 2.1100254701 0.5697765734 -0.4557291637 0.5030609848 -0.5365588207
[86] 2.5302508073 0.1654886594 -1.2576489132 0.7056407279 0.4729848845
[91] -2.1217322670 -1.0410798386 0.1338956520 1.2225372627 1.6905431172
[96] 0.1739593419 0.6789511418 1.3417585203 -0.0666142353 -0.4140724400
> 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] 0.7976614449 -1.2575368953 0.2334617144 -0.5390310938 -0.3032363193
[6] -0.1251638340 1.2920972872 0.4426417110 -0.3204030282 0.6208987936
[11] 0.9528292793 1.2195944700 -0.7536693822 1.6741329212 0.0514828239
[16] -1.3104392298 -1.1353261740 -0.7781482774 -0.4319665172 1.0002697768
[21] 0.6504770483 1.5290070477 -0.9160970763 -0.9411092813 1.4185913621
[26] 0.1570323145 0.9828201286 1.1619904388 0.5231244093 -0.4973783370
[31] -0.0002813796 -1.8197856389 -1.6479691975 -0.3283955108 -0.7233960555
[36] -2.0261919053 2.8266842406 -0.4234423550 -1.0413722342 -1.0313668971
[41] 0.5813499456 -0.5672738901 1.1034697951 -0.2273929450 1.3043246048
[46] 0.3448917809 0.8414990485 1.6232117136 -1.6322234262 -0.3334772950
[51] -0.6702078756 -0.1298583196 0.1728347137 0.2391782739 -0.0948429116
[56] 1.4629522319 1.3543415934 0.2654116345 -0.6439977221 2.3890608444
[61] 0.4343796525 0.6336823705 -0.0942712632 -0.1329281034 2.0322354883
[66] -0.5540766541 1.1144670597 -1.6880750574 -1.0406707663 0.5170928254
[71] -0.1821217394 0.8460626106 0.6500223498 0.8978831906 -0.4550459878
[76] -0.6888255265 0.6643134895 -1.2927318811 0.2077209663 -0.7589686896
[81] 2.1100254701 0.5697765734 -0.4557291637 0.5030609848 -0.5365588207
[86] 2.5302508073 0.1654886594 -1.2576489132 0.7056407279 0.4729848845
[91] -2.1217322670 -1.0410798386 0.1338956520 1.2225372627 1.6905431172
[96] 0.1739593419 0.6789511418 1.3417585203 -0.0666142353 -0.4140724400
> rowMin(tmp2)
[1] 0.7976614449 -1.2575368953 0.2334617144 -0.5390310938 -0.3032363193
[6] -0.1251638340 1.2920972872 0.4426417110 -0.3204030282 0.6208987936
[11] 0.9528292793 1.2195944700 -0.7536693822 1.6741329212 0.0514828239
[16] -1.3104392298 -1.1353261740 -0.7781482774 -0.4319665172 1.0002697768
[21] 0.6504770483 1.5290070477 -0.9160970763 -0.9411092813 1.4185913621
[26] 0.1570323145 0.9828201286 1.1619904388 0.5231244093 -0.4973783370
[31] -0.0002813796 -1.8197856389 -1.6479691975 -0.3283955108 -0.7233960555
[36] -2.0261919053 2.8266842406 -0.4234423550 -1.0413722342 -1.0313668971
[41] 0.5813499456 -0.5672738901 1.1034697951 -0.2273929450 1.3043246048
[46] 0.3448917809 0.8414990485 1.6232117136 -1.6322234262 -0.3334772950
[51] -0.6702078756 -0.1298583196 0.1728347137 0.2391782739 -0.0948429116
[56] 1.4629522319 1.3543415934 0.2654116345 -0.6439977221 2.3890608444
[61] 0.4343796525 0.6336823705 -0.0942712632 -0.1329281034 2.0322354883
[66] -0.5540766541 1.1144670597 -1.6880750574 -1.0406707663 0.5170928254
[71] -0.1821217394 0.8460626106 0.6500223498 0.8978831906 -0.4550459878
[76] -0.6888255265 0.6643134895 -1.2927318811 0.2077209663 -0.7589686896
[81] 2.1100254701 0.5697765734 -0.4557291637 0.5030609848 -0.5365588207
[86] 2.5302508073 0.1654886594 -1.2576489132 0.7056407279 0.4729848845
[91] -2.1217322670 -1.0410798386 0.1338956520 1.2225372627 1.6905431172
[96] 0.1739593419 0.6789511418 1.3417585203 -0.0666142353 -0.4140724400
>
> colMeans(tmp2)
[1] 0.1408192
> colSums(tmp2)
[1] 14.08192
> colVars(tmp2)
[1] 1.082989
> colSd(tmp2)
[1] 1.040668
> colMax(tmp2)
[1] 2.826684
> colMin(tmp2)
[1] -2.121732
> colMedians(tmp2)
[1] 0.1612605
> colRanges(tmp2)
[,1]
[1,] -2.121732
[2,] 2.826684
>
> dataset1 <- matrix(dataset1,1,100)
>
> agree.checks(tmp,dataset1)
>
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>
>
> tmp <- createBufferedMatrix(10,10)
>
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
[1] 2.6189775 -1.6129432 -2.5261808 1.9868705 0.1073277 -4.4471777
[7] 1.4716225 1.9499566 -6.6820872 -3.2451111
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.8831453
[2,] -0.6053791
[3,] 0.3571460
[4,] 0.9932893
[5,] 2.8764459
>
> rowApply(tmp,sum)
[1] -6.8172713066 -5.7794823911 2.7319570151 0.0005465904 -1.5332043681
[6] 2.7427601980 1.9736601107 -3.6183152570 0.8819708591 -0.9613667007
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 10 10 8 1 10 1 6 6 3 4
[2,] 5 9 4 8 2 9 5 3 5 3
[3,] 1 1 10 4 8 5 10 7 8 1
[4,] 8 8 7 7 3 4 9 5 6 10
[5,] 7 5 6 5 1 8 7 2 9 7
[6,] 3 4 1 6 4 10 3 1 4 6
[7,] 6 7 9 10 7 3 4 4 1 9
[8,] 9 6 5 2 9 2 8 8 10 8
[9,] 2 2 2 9 6 6 1 9 2 2
[10,] 4 3 3 3 5 7 2 10 7 5
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -0.3734690 3.1734021 -2.1991934 0.3117554 1.2328364 2.4773198
[7] -4.2912460 -3.0995415 -0.6720699 -2.4802047 1.4463934 -2.6326067
[13] -1.3576742 1.8007569 -5.8204205 1.1207564 1.2890348 0.4528402
[19] 2.3400360 -1.6582699
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.9314761
[2,] -0.5555473
[3,] 0.1221668
[4,] 0.1462020
[5,] 0.8451856
>
> rowApply(tmp,sum)
[1] -6.452224 -1.073647 2.146257 -5.597453 2.037503
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 9 12 16 6 11
[2,] 14 17 19 19 2
[3,] 13 4 17 1 10
[4,] 17 13 12 5 7
[5,] 5 16 18 16 8
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -0.5555473 0.3144336 0.12978689 0.9647630 -1.35058098 0.6672719
[2,] 0.1221668 1.0080764 -0.87403530 0.1224877 0.82382910 0.7438214
[3,] 0.8451856 1.2913139 1.07774535 0.3688987 1.19076016 -1.3764650
[4,] -0.9314761 1.3249955 -2.59221550 -0.9980222 0.61704081 1.5119290
[5,] 0.1462020 -0.7654172 0.05952517 -0.1463718 -0.04821274 0.9307626
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -2.0446911 -2.2875872 1.0682035 0.01500324 -1.98851119 -0.5245264
[2,] -1.2061994 -1.7523062 -1.2160368 0.41478757 -0.19978672 -0.8715476
[3,] -1.4688058 0.6316178 0.2961970 -0.37795826 0.02616647 -0.1179678
[4,] -0.6622424 -0.2499998 -1.0026231 -2.15088432 0.93999175 -0.5290736
[5,] 1.0906928 0.5587339 0.1821895 -0.38115291 2.66853313 -0.5894913
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 1.16081138 1.36792035 -1.289147 -0.08594066 -0.6624616 -0.6261917
[2,] -0.41403500 -0.59104656 1.527124 1.44914142 -0.5364978 -0.4984308
[3,] -1.53621890 0.63576719 -1.439729 -0.12921950 0.6911368 0.1489294
[4,] -0.01865003 0.36729880 -2.001868 -0.27606758 1.1552298 0.2970545
[5,] -0.54958166 0.02081716 -2.616801 0.16284273 0.6416276 1.1314787
[,19] [,20]
[1,] 0.73361876 -1.4588511
[2,] -0.29724764 1.1720886
[3,] 1.52111779 -0.1322158
[4,] 0.09923797 -0.4971086
[5,] 0.28330917 -0.7421831
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.21-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-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 649 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 562 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 1.095096 -0.3250792 -0.3920108 -0.2835622 -1.029935 1.807829 -0.3380645
col8 col9 col10 col11 col12 col13 col14
row1 -0.6495735 -0.3740537 1.009107 0.2398415 -0.8493229 -0.4866743 0.4970259
col15 col16 col17 col18 col19 col20
row1 0.281381 1.285866 1.054663 -0.821194 -0.4473865 -1.770134
> tmp[,"col10"]
col10
row1 1.009107376
row2 1.964976843
row3 -0.506955314
row4 -0.009168832
row5 -0.315518605
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 1.09509620 -0.3250792 -0.3920108 -0.2835622 -1.0299353 1.807829 -0.3380645
row5 0.09691852 -0.2857753 0.4687197 -0.8032733 -0.5101975 1.063830 -0.1458525
col8 col9 col10 col11 col12 col13
row1 -0.6495735 -0.3740537 1.0091074 0.2398415 -0.8493229 -0.4866743
row5 0.2556179 -0.4989090 -0.3155186 0.5478078 -0.5755873 -1.5044277
col14 col15 col16 col17 col18 col19 col20
row1 0.4970259 0.281381 1.285866 1.0546631 -0.8211940 -0.4473865 -1.770134
row5 -0.1307291 1.002530 1.148027 0.6144071 -0.0611371 1.7657986 1.114025
> tmp[,c("col6","col20")]
col6 col20
row1 1.8078288 -1.7701344
row2 1.3263038 -0.6993058
row3 -0.2853995 -0.4654967
row4 -1.2671616 -0.3265293
row5 1.0638301 1.1140249
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 1.807829 -1.770134
row5 1.063830 1.114025
>
>
>
>
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105)
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.11752 49.40301 49.54987 49.58291 50.20872 105.805 52.37102 51.51475
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.68869 48.6201 49.56159 48.09588 50.02667 49.20227 49.47693 50.01065
col17 col18 col19 col20
row1 52.38774 49.66092 52.14357 103.9695
> tmp[,"col10"]
col10
row1 48.62010
row2 28.20005
row3 29.38313
row4 31.10293
row5 50.45866
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.11752 49.40301 49.54987 49.58291 50.20872 105.8050 52.37102 51.51475
row5 49.81038 49.65729 49.18567 49.08518 50.37673 104.3426 49.80765 48.70704
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.68869 48.62010 49.56159 48.09588 50.02667 49.20227 49.47693 50.01065
row5 51.84850 50.45866 47.57112 50.26243 48.35040 48.86940 49.24358 50.68397
col17 col18 col19 col20
row1 52.38774 49.66092 52.14357 103.9695
row5 49.78653 48.75440 50.62223 103.4955
> tmp[,c("col6","col20")]
col6 col20
row1 105.80504 103.96953
row2 75.99990 75.10261
row3 76.95144 75.48269
row4 75.03374 75.19777
row5 104.34264 103.49553
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.8050 103.9695
row5 104.3426 103.4955
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.8050 103.9695
row5 104.3426 103.4955
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -0.2693996
[2,] -0.6028831
[3,] 0.7855373
[4,] -0.8913048
[5,] -0.3109250
> tmp[,c("col17","col7")]
col17 col7
[1,] -1.1443238 0.4439894
[2,] -0.8515888 -0.5804910
[3,] -1.2669018 -0.1713060
[4,] -2.0429971 1.1042095
[5,] 0.6009649 -0.6914333
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.9538482 0.1486920
[2,] -2.4050168 1.4120612
[3,] -0.4539150 0.3784100
[4,] -0.8264679 -0.6506217
[5,] -0.2104551 -0.5365796
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.9538482
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.9538482
[2,] -2.4050168
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row3 -0.9632514 -0.554666 0.3577836 -0.5790516 -0.3927148 -0.18939938 1.253609
row1 -0.4167480 -1.110486 -0.7071684 -1.2887514 0.9596130 0.07114093 1.419203
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row3 -1.312251 -0.02810493 -0.3533841 0.3129505 -2.1332794 0.2963671 -0.6481955
row1 -1.911532 -1.00958103 0.9657890 0.8549715 -0.1586905 0.5834766 0.2618871
[,15] [,16] [,17] [,18] [,19] [,20]
row3 -0.7960722 -0.5199614 -0.8373746 0.04210276 -0.1096002 0.5473868
row1 1.4987635 -0.2466139 -1.5040563 -0.77166764 0.1440363 1.0121679
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.9204365 -2.301505 0.5313908 1.817532 -0.08340382 1.007363 -0.2568127
[,8] [,9] [,10]
row2 0.609881 0.5210246 -0.153139
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8]
row5 -1.585164 0.279515 0.4991652 1.290348 1.056539 0.339459 -1.714814 1.046798
[,9] [,10] [,11] [,12] [,13] [,14] [,15]
row5 2.483531 0.5083054 0.3662843 -1.987352 -0.1036256 0.6053252 -0.5233082
[,16] [,17] [,18] [,19] [,20]
row5 -1.012888 0.3553805 2.681153 -1.721402 -0.3076612
>
>
> 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: 0x600003b04420>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM625513d6a2ed"
[2] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM625570627fc7"
[3] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM625552b31b75"
[4] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM62556ccfc8bd"
[5] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM62553d84281a"
[6] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM62552f64e283"
[7] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM62558531ec4"
[8] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM6255908da21"
[9] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM62552428b129"
[10] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM62556b870d4a"
[11] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM62556f79ac6c"
[12] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM62551d271fa1"
[13] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM6255738d91fa"
[14] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM6255536aef5a"
[15] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM62551188287f"
>
>
> ### 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: 0x600003bb0060>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x600003bb0060>
Warning message:
In dir.create(new.directory) :
'/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x600003bb0060>
> rowMedians(tmp)
[1] -0.549494191 0.092290094 0.039427362 -0.243820708 0.012617790
[6] 0.334345994 0.115995116 0.075044214 0.007911534 0.080908474
[11] 0.095508228 0.333405122 0.515107842 -0.171394798 0.193489148
[16] 0.503925612 0.551766844 -0.054936100 -0.481904922 -0.314714289
[21] 0.471412127 -0.044177416 0.476673916 0.475767467 -0.310438406
[26] 0.020678947 -0.261753127 -0.084521599 0.563964940 -0.065781537
[31] 0.047116102 -0.141504076 -0.009588035 0.132849524 -0.193819926
[36] 0.711655903 0.040120048 -0.137327931 0.046686185 -0.403374880
[41] 0.277488197 -0.176486184 -0.176238814 -0.283574243 0.012828882
[46] 0.730306015 -0.414582552 0.215501683 0.039098661 0.113085475
[51] -0.305307217 0.445182601 0.132070553 -0.100387045 -0.565450857
[56] -0.093323323 0.094565310 0.193407487 -0.095293353 -0.186560521
[61] 0.325127827 0.322205097 -0.213835063 0.002519697 0.011999546
[66] -0.084142204 0.355483541 0.557299925 -0.610774385 0.308894725
[71] 0.083258994 0.022787612 0.122123439 -0.478465468 -0.035088237
[76] 0.008920895 0.200726971 -0.052916706 -0.761687161 0.049400457
[81] -0.227361809 -0.028334917 -0.490114730 0.187147355 -0.131567174
[86] -0.148716251 0.061315075 -0.185129545 -0.356759318 0.581512005
[91] 0.275387627 -0.241948829 0.191321287 -0.003225681 -0.010900498
[96] 0.721082163 0.114153636 0.052862384 -0.022275300 -0.340546488
[101] 0.147737030 0.454143981 0.431374464 -0.013300475 0.181783130
[106] -0.040157240 0.031754285 0.629849225 0.533915300 -0.445927169
[111] -0.499820976 -0.049819836 0.195128627 0.307015217 -0.365405060
[116] 0.100642632 0.166812615 -0.227579770 -0.492517640 -0.095168172
[121] 0.177469274 0.552258239 -0.335119533 -0.195477521 -0.149661529
[126] 0.274586711 -0.319431961 0.177401855 0.167481736 0.149666618
[131] 0.247469645 -0.043520790 -0.563103323 0.291035952 -0.350550247
[136] -0.130902484 -0.323360238 -0.144082453 -0.140700081 0.271347066
[141] -0.362812794 -0.244877334 -0.094619194 0.109761547 0.541426583
[146] 0.318298883 0.718680814 -0.442064871 -0.690609428 0.093573454
[151] -0.326216581 0.239800169 0.548962562 -0.229405686 0.281186514
[156] -0.114763091 0.071735608 -0.104536455 0.125221060 0.686715129
[161] 0.181399161 0.207523277 0.058512940 -0.492627472 0.292813918
[166] -0.195272540 -0.554502494 0.141456410 0.280340828 -0.201197635
[171] -0.233889511 0.312740466 -0.166362695 0.149699109 -0.227100446
[176] 0.199089816 -0.129835669 0.331868400 -0.258038696 0.218166815
[181] 0.155542532 -0.113721437 0.031058077 -0.233646513 0.697991180
[186] 0.017168981 0.003313714 -0.140515709 -0.012868351 -0.559534118
[191] 0.513928591 -0.197212076 -0.349952203 0.060484720 0.467971023
[196] -0.334683497 -0.321965420 0.194542948 -0.140731173 -0.102370099
[201] -0.120151013 -0.686640715 0.310407720 -0.054611893 0.081067242
[206] -0.016709876 0.328165180 -0.319119911 0.766446082 0.315397710
[211] 0.069188038 0.638912474 0.585589536 -0.673102321 -0.400410597
[216] -0.240237452 0.390092976 -0.520991497 0.128577258 -0.093764988
[221] -0.637493079 0.765649420 0.336600357 -0.116301061 0.049133174
[226] -0.022117340 -0.048960536 -0.362591558 -0.027944585 0.299375312
>
> proc.time()
user system elapsed
2.721 16.766 20.121
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.5.0 RC (2025-04-04 r88126) -- "How About a Twenty-Six"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> prefix <- "dbmtest"
> directory <- getwd()
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_Test_C",P)
RBufferedMatrix
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1
Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000
1.000000 2.000000 3.000000 4.000000 5.000000
2.000000 3.000000 4.000000 5.000000 6.000000
3.000000 4.000000 5.000000 6.000000 7.000000
4.000000 5.000000 6.000000 7.000000 8.000000
<pointer: 0x6000006a00c0>
> .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: 0x6000006a00c0>
> .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: 0x6000006a00c0>
> .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: 0x6000006a00c0>
> 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: 0x600000694000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600000694000>
> .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: 0x600000694000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600000694000>
> .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: 0x600000694000>
> 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: 0x6000006c8180>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000006c8180>
> .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: 0x6000006c8180>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x6000006c8180>
> .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: 0x6000006c8180>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x6000006c8180>
> .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: 0x6000006c8180>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x6000006c8180>
> .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: 0x6000006c8180>
> 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: 0x6000006e0060>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x6000006e0060>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000006e0060>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000006e0060>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile672d4ab363a6" "BufferedMatrixFile672d529557bd"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile672d4ab363a6" "BufferedMatrixFile672d529557bd"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000006e4060>
> .Call("R_bm_AddColumn",P)
<pointer: 0x6000006e4060>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x6000006e4060>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x6000006e4060>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x6000006e4060>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x6000006e4060>
> .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: 0x600000680000>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600000680000>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600000680000>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x600000680000>
> 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: 0x6000006e41e0>
> .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: 0x6000006e41e0>
> rm(P)
>
> proc.time()
user system elapsed
0.362 0.168 0.519
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.5.0 RC (2025-04-04 r88126) -- "How About a Twenty-Six"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
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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
0.350 0.097 0.454