Ben Bolstad
| Snapshot Date: 2025-09-02 13:45 -0400 (Tue, 02 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 2025-09-03 12:07 -0400 (Wed, 03 Sep 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 24.04.3 LTS) | x86_64 | 4.5.1 (2025-06-13) -- "Great Square Root" | 4826 |
| lconway | macOS 12.7.1 Monterey | x86_64 | 4.5.1 (2025-06-13) -- "Great Square Root" | 4616 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | 4.5.1 Patched (2025-06-14 r88325) -- "Great Square Root" | 4563 |
| taishan | Linux (openEuler 24.03 LTS) | aarch64 | 4.5.0 (2025-04-11) -- "How About a Twenty-Six" | 4541 |
| 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 252/2321 | 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. - See Martin Grigorov's blog post for how to debug Linux ARM64 related issues on a x86_64 host. |
| Package: BufferedMatrix |
| Version: 1.73.0 |
| Command: /home/biocbuild/R/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/R/R/site-library --no-vignettes --timings BufferedMatrix_1.73.0.tar.gz |
| StartedAt: 2025-09-02 04:57:31 -0000 (Tue, 02 Sep 2025) |
| EndedAt: 2025-09-02 04:57:54 -0000 (Tue, 02 Sep 2025) |
| EllapsedTime: 23.0 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
##############################################################################
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###
### Running command:
###
### /home/biocbuild/R/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/R/R/site-library --no-vignettes --timings BufferedMatrix_1.73.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.5.0 (2025-04-11)
* using platform: aarch64-unknown-linux-gnu
* R was compiled by
aarch64-unknown-linux-gnu-gcc (GCC) 14.2.0
GNU Fortran (GCC) 14.2.0
* running under: openEuler 24.03 (LTS)
* 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 ... OK
* used C compiler: ‘aarch64-unknown-linux-gnu-gcc (GCC) 14.2.0’
* 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 loading without being on the library search path ... 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 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: 2 NOTEs
See
‘/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/R/R/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library ‘/home/biocbuild/R/R-4.5.0/site-library’
* installing *source* package ‘BufferedMatrix’ ...
** this is package ‘BufferedMatrix’ version ‘1.73.0’
** using staged installation
** libs
using C compiler: ‘aarch64-unknown-linux-gnu-gcc (GCC) 14.2.0’
/opt/ohpc/pub/compiler/gcc/14.2.0/bin/aarch64-unknown-linux-gnu-gcc -std=gnu23 -I"/home/biocbuild/R/R-4.5.0/include" -DNDEBUG -I/usr/local/include -fPIC -g -O2 -Wall -Werror=format-security -c RBufferedMatrix.c -o RBufferedMatrix.o
/opt/ohpc/pub/compiler/gcc/14.2.0/bin/aarch64-unknown-linux-gnu-gcc -std=gnu23 -I"/home/biocbuild/R/R-4.5.0/include" -DNDEBUG -I/usr/local/include -fPIC -g -O2 -Wall -Werror=format-security -c doubleBufferedMatrix.c -o doubleBufferedMatrix.o
doubleBufferedMatrix.c: In function ‘dbm_ReadOnlyMode’:
doubleBufferedMatrix.c:1580:7: warning: suggest parentheses around operand of ‘!’ or change ‘&’ to ‘&&’ or ‘!’ to ‘~’ [-Wparentheses]
1580 | if (!(Matrix->readonly) & setting){
| ^~~~~~~~~~~~~~~~~~~
doubleBufferedMatrix.c: At top level:
doubleBufferedMatrix.c:3327:12: warning: ‘sort_double’ defined but not used [-Wunused-function]
3327 | static int sort_double(const double *a1,const double *a2){
| ^~~~~~~~~~~
/opt/ohpc/pub/compiler/gcc/14.2.0/bin/aarch64-unknown-linux-gnu-gcc -std=gnu23 -I"/home/biocbuild/R/R-4.5.0/include" -DNDEBUG -I/usr/local/include -fPIC -g -O2 -Wall -Werror=format-security -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
/opt/ohpc/pub/compiler/gcc/14.2.0/bin/aarch64-unknown-linux-gnu-gcc -std=gnu23 -I"/home/biocbuild/R/R-4.5.0/include" -DNDEBUG -I/usr/local/include -fPIC -g -O2 -Wall -Werror=format-security -c init_package.c -o init_package.o
/opt/ohpc/pub/compiler/gcc/14.2.0/bin/aarch64-unknown-linux-gnu-gcc -std=gnu23 -shared -L/home/biocbuild/R/R-4.5.0/lib -L/usr/local/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -L/home/biocbuild/R/R-4.5.0/lib -lR
installing to /home/biocbuild/R/R-4.5.0/site-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 (2025-04-11) -- "How About a Twenty-Six"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu
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
0.325 0.052 0.363
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.5.0 (2025-04-11) -- "How About a Twenty-Six"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu
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] "/home/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) max used (Mb)
Ncells 478398 25.6 1047041 56 639620 34.2
Vcells 885166 6.8 8388608 64 2080985 15.9
>
>
>
>
> ##
> ## 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] "Tue Sep 2 04:57:48 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] "Tue Sep 2 04:57:48 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: 0x3ec66ff0>
>
>
>
> 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] "Tue Sep 2 04:57:48 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] "Tue Sep 2 04:57:48 2025"
>
> ColMode(tmp2)
<pointer: 0x3ec66ff0>
>
>
>
> ### 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,] 101.8365846 -1.0828884 1.102423 -0.4476086
[2,] -1.1089254 0.1047039 -1.316631 0.3326882
[3,] -0.5309606 -0.7290781 1.418141 2.0695633
[4,] -1.4385907 2.0618473 1.689147 0.5621949
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 101.8365846 1.0828884 1.102423 0.4476086
[2,] 1.1089254 0.1047039 1.316631 0.3326882
[3,] 0.5309606 0.7290781 1.418141 2.0695633
[4,] 1.4385907 2.0618473 1.689147 0.5621949
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 10.0914114 1.0406192 1.049963 0.6690356
[2,] 1.0530553 0.3235798 1.147445 0.5767913
[3,] 0.7286704 0.8538607 1.190857 1.4385977
[4,] 1.1994126 1.4359134 1.299672 0.7497966
>
> 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: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 2 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 227.75070 36.48908 36.60206 32.13796
[2,] 36.63948 28.34050 37.79109 31.10060
[3,] 32.81766 34.26769 38.32671 41.45554
[4,] 38.43272 41.42098 39.68587 33.06016
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x3fe969a0>
> exp(tmp5)
<pointer: 0x3fe969a0>
> log(tmp5,2)
<pointer: 0x3fe969a0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 474.0332
> Min(tmp5)
[1] 54.5437
> mean(tmp5)
[1] 73.15492
> Sum(tmp5)
[1] 14630.98
> Var(tmp5)
[1] 882.0031
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 92.80782 70.66561 72.05119 69.45227 74.51867 71.03520 70.26589 68.73220
[9] 70.73588 71.28448
> rowSums(tmp5)
[1] 1856.156 1413.312 1441.024 1389.045 1490.373 1420.704 1405.318 1374.644
[9] 1414.718 1425.690
> rowVars(tmp5)
[1] 8102.05418 56.72302 101.51898 77.01935 69.51319 113.70946
[7] 64.77023 54.37055 57.75914 65.67769
> rowSd(tmp5)
[1] 90.011411 7.531469 10.075663 8.776067 8.337457 10.663464 8.047995
[8] 7.373639 7.599943 8.104178
> rowMax(tmp5)
[1] 474.03324 85.92648 90.61489 86.21235 89.83466 91.75523 85.67497
[8] 80.01239 82.79650 85.26531
> rowMin(tmp5)
[1] 56.77222 58.98704 57.85886 54.54370 57.13715 56.46427 57.09088 56.39168
[9] 57.26221 59.02311
>
> colMeans(tmp5)
[1] 113.49967 69.92635 72.19995 74.98725 69.11882 70.16549 69.15328
[8] 69.17091 72.78729 70.83100 73.25789 70.54012 70.96391 67.85757
[15] 68.20791 76.29280 74.80150 68.92036 71.18729 69.22908
> colSums(tmp5)
[1] 1134.9967 699.2635 721.9995 749.8725 691.1882 701.6549 691.5328
[8] 691.7091 727.8729 708.3100 732.5789 705.4012 709.6391 678.5757
[15] 682.0791 762.9280 748.0150 689.2036 711.8729 692.2908
> colVars(tmp5)
[1] 16103.37358 104.50579 75.80364 75.86048 55.99561 53.47285
[7] 27.85201 114.13037 82.32093 50.58391 68.20683 121.09525
[13] 65.85542 65.11800 49.33305 63.03831 82.90240 68.32005
[19] 66.14991 87.04463
> colSd(tmp5)
[1] 126.899068 10.222807 8.706529 8.709792 7.483021 7.312513
[7] 5.277500 10.683182 9.073088 7.112237 8.258742 11.004329
[13] 8.115135 8.069572 7.023749 7.939667 9.105076 8.265594
[19] 8.133259 9.329771
> colMax(tmp5)
[1] 474.03324 86.21235 82.60093 91.75523 78.64947 79.28954 80.81194
[8] 85.92648 85.67497 79.21988 84.40460 90.61489 79.49282 77.94441
[15] 78.47368 84.91930 88.42336 80.84863 80.38279 85.26531
> colMin(tmp5)
[1] 63.92228 57.13715 60.35056 64.73183 56.77222 57.49741 62.14415 54.54370
[9] 60.02824 57.03389 59.29399 57.76426 57.42380 56.39168 57.09088 62.57290
[17] 59.10174 57.26221 56.99512 56.46427
>
>
> ### setting a random element to NA and then testing with na.rm=TRUE or na.rm=FALSE (The default)
>
>
> which.row <- sample(1:10,1,replace=TRUE)
> which.col <- sample(1:20,1,replace=TRUE)
>
> tmp5[which.row,which.col] <- NA
>
> Max(tmp5)
[1] NA
> Min(tmp5)
[1] NA
> mean(tmp5)
[1] NA
> Sum(tmp5)
[1] NA
> Var(tmp5)
[1] NA
>
> rowMeans(tmp5)
[1] 92.80782 70.66561 72.05119 69.45227 NA 71.03520 70.26589 68.73220
[9] 70.73588 71.28448
> rowSums(tmp5)
[1] 1856.156 1413.312 1441.024 1389.045 NA 1420.704 1405.318 1374.644
[9] 1414.718 1425.690
> rowVars(tmp5)
[1] 8102.05418 56.72302 101.51898 77.01935 70.34500 113.70946
[7] 64.77023 54.37055 57.75914 65.67769
> rowSd(tmp5)
[1] 90.011411 7.531469 10.075663 8.776067 8.387193 10.663464 8.047995
[8] 7.373639 7.599943 8.104178
> rowMax(tmp5)
[1] 474.03324 85.92648 90.61489 86.21235 NA 91.75523 85.67497
[8] 80.01239 82.79650 85.26531
> rowMin(tmp5)
[1] 56.77222 58.98704 57.85886 54.54370 NA 56.46427 57.09088 56.39168
[9] 57.26221 59.02311
>
> colMeans(tmp5)
[1] 113.49967 69.92635 72.19995 74.98725 69.11882 70.16549 69.15328
[8] 69.17091 72.78729 70.83100 73.25789 NA 70.96391 67.85757
[15] 68.20791 76.29280 74.80150 68.92036 71.18729 69.22908
> colSums(tmp5)
[1] 1134.9967 699.2635 721.9995 749.8725 691.1882 701.6549 691.5328
[8] 691.7091 727.8729 708.3100 732.5789 NA 709.6391 678.5757
[15] 682.0791 762.9280 748.0150 689.2036 711.8729 692.2908
> colVars(tmp5)
[1] 16103.37358 104.50579 75.80364 75.86048 55.99561 53.47285
[7] 27.85201 114.13037 82.32093 50.58391 68.20683 NA
[13] 65.85542 65.11800 49.33305 63.03831 82.90240 68.32005
[19] 66.14991 87.04463
> colSd(tmp5)
[1] 126.899068 10.222807 8.706529 8.709792 7.483021 7.312513
[7] 5.277500 10.683182 9.073088 7.112237 8.258742 NA
[13] 8.115135 8.069572 7.023749 7.939667 9.105076 8.265594
[19] 8.133259 9.329771
> colMax(tmp5)
[1] 474.03324 86.21235 82.60093 91.75523 78.64947 79.28954 80.81194
[8] 85.92648 85.67497 79.21988 84.40460 NA 79.49282 77.94441
[15] 78.47368 84.91930 88.42336 80.84863 80.38279 85.26531
> colMin(tmp5)
[1] 63.92228 57.13715 60.35056 64.73183 56.77222 57.49741 62.14415 54.54370
[9] 60.02824 57.03389 59.29399 NA 57.42380 56.39168 57.09088 62.57290
[17] 59.10174 57.26221 56.99512 56.46427
>
> Max(tmp5,na.rm=TRUE)
[1] 474.0332
> Min(tmp5,na.rm=TRUE)
[1] 54.5437
> mean(tmp5,na.rm=TRUE)
[1] 73.1119
> Sum(tmp5,na.rm=TRUE)
[1] 14549.27
> Var(tmp5,na.rm=TRUE)
[1] 886.0856
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 92.80782 70.66561 72.05119 69.45227 74.13982 71.03520 70.26589 68.73220
[9] 70.73588 71.28448
> rowSums(tmp5,na.rm=TRUE)
[1] 1856.156 1413.312 1441.024 1389.045 1408.657 1420.704 1405.318 1374.644
[9] 1414.718 1425.690
> rowVars(tmp5,na.rm=TRUE)
[1] 8102.05418 56.72302 101.51898 77.01935 70.34500 113.70946
[7] 64.77023 54.37055 57.75914 65.67769
> rowSd(tmp5,na.rm=TRUE)
[1] 90.011411 7.531469 10.075663 8.776067 8.387193 10.663464 8.047995
[8] 7.373639 7.599943 8.104178
> rowMax(tmp5,na.rm=TRUE)
[1] 474.03324 85.92648 90.61489 86.21235 89.83466 91.75523 85.67497
[8] 80.01239 82.79650 85.26531
> rowMin(tmp5,na.rm=TRUE)
[1] 56.77222 58.98704 57.85886 54.54370 57.13715 56.46427 57.09088 56.39168
[9] 57.26221 59.02311
>
> colMeans(tmp5,na.rm=TRUE)
[1] 113.49967 69.92635 72.19995 74.98725 69.11882 70.16549 69.15328
[8] 69.17091 72.78729 70.83100 73.25789 69.29826 70.96391 67.85757
[15] 68.20791 76.29280 74.80150 68.92036 71.18729 69.22908
> colSums(tmp5,na.rm=TRUE)
[1] 1134.9967 699.2635 721.9995 749.8725 691.1882 701.6549 691.5328
[8] 691.7091 727.8729 708.3100 732.5789 623.6843 709.6391 678.5757
[15] 682.0791 762.9280 748.0150 689.2036 711.8729 692.2908
> colVars(tmp5,na.rm=TRUE)
[1] 16103.37358 104.50579 75.80364 75.86048 55.99561 53.47285
[7] 27.85201 114.13037 82.32093 50.58391 68.20683 118.88233
[13] 65.85542 65.11800 49.33305 63.03831 82.90240 68.32005
[19] 66.14991 87.04463
> colSd(tmp5,na.rm=TRUE)
[1] 126.899068 10.222807 8.706529 8.709792 7.483021 7.312513
[7] 5.277500 10.683182 9.073088 7.112237 8.258742 10.903317
[13] 8.115135 8.069572 7.023749 7.939667 9.105076 8.265594
[19] 8.133259 9.329771
> colMax(tmp5,na.rm=TRUE)
[1] 474.03324 86.21235 82.60093 91.75523 78.64947 79.28954 80.81194
[8] 85.92648 85.67497 79.21988 84.40460 90.61489 79.49282 77.94441
[15] 78.47368 84.91930 88.42336 80.84863 80.38279 85.26531
> colMin(tmp5,na.rm=TRUE)
[1] 63.92228 57.13715 60.35056 64.73183 56.77222 57.49741 62.14415 54.54370
[9] 60.02824 57.03389 59.29399 57.76426 57.42380 56.39168 57.09088 62.57290
[17] 59.10174 57.26221 56.99512 56.46427
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 92.80782 70.66561 72.05119 69.45227 NaN 71.03520 70.26589 68.73220
[9] 70.73588 71.28448
> rowSums(tmp5,na.rm=TRUE)
[1] 1856.156 1413.312 1441.024 1389.045 0.000 1420.704 1405.318 1374.644
[9] 1414.718 1425.690
> rowVars(tmp5,na.rm=TRUE)
[1] 8102.05418 56.72302 101.51898 77.01935 NA 113.70946
[7] 64.77023 54.37055 57.75914 65.67769
> rowSd(tmp5,na.rm=TRUE)
[1] 90.011411 7.531469 10.075663 8.776067 NA 10.663464 8.047995
[8] 7.373639 7.599943 8.104178
> rowMax(tmp5,na.rm=TRUE)
[1] 474.03324 85.92648 90.61489 86.21235 NA 91.75523 85.67497
[8] 80.01239 82.79650 85.26531
> rowMin(tmp5,na.rm=TRUE)
[1] 56.77222 58.98704 57.85886 54.54370 NA 56.46427 57.09088 56.39168
[9] 57.26221 59.02311
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 116.12911 71.34737 71.75215 74.56525 69.62350 69.89333 67.85787
[8] 68.03446 74.20496 70.33735 72.72015 NaN 70.07325 67.66131
[15] 68.97746 76.07324 74.81429 68.46870 70.60499 67.63087
> colSums(tmp5,na.rm=TRUE)
[1] 1045.1620 642.1264 645.7694 671.0873 626.6115 629.0400 610.7208
[8] 612.3101 667.8446 633.0362 654.4814 0.0000 630.6592 608.9518
[15] 620.7972 684.6592 673.3286 616.2183 635.4449 608.6778
> colVars(tmp5,na.rm=TRUE)
[1] 18038.51299 94.85183 83.02320 83.33966 60.12959 59.32363
[7] 12.45513 113.86707 70.00085 54.16540 73.47964 NA
[13] 65.16287 72.82445 48.83740 70.37577 93.26336 74.56507
[19] 70.60402 69.18973
> colSd(tmp5,na.rm=TRUE)
[1] 134.307531 9.739190 9.111707 9.129056 7.754327 7.702184
[7] 3.529182 10.670851 8.366651 7.359715 8.572027 NA
[13] 8.072352 8.533724 6.988376 8.389027 9.657296 8.635107
[19] 8.402620 8.318036
> colMax(tmp5,na.rm=TRUE)
[1] 474.03324 86.21235 82.60093 91.75523 78.64947 79.28954 73.53544
[8] 85.92648 85.67497 79.21988 84.40460 -Inf 79.49282 77.94441
[15] 78.47368 84.91930 88.42336 80.84863 80.38279 85.26531
> colMin(tmp5,na.rm=TRUE)
[1] 63.92228 58.98704 60.35056 64.73183 56.77222 57.49741 62.14415 54.54370
[9] 60.22291 57.03389 59.29399 Inf 57.42380 56.39168 57.09088 62.57290
[17] 59.10174 57.26221 56.99512 56.46427
>
>
>
>
> 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] 123.9353 247.1449 375.1097 253.5872 261.8499 163.9990 125.5222 229.0322
[9] 193.7590 139.1237
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 123.9353 247.1449 375.1097 253.5872 261.8499 163.9990 125.5222 229.0322
[9] 193.7590 139.1237
>
>
>
> 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] -1.705303e-13 -2.273737e-13 -2.842171e-14 -1.421085e-13 0.000000e+00
[6] 1.136868e-13 5.684342e-14 -1.136868e-13 -2.842171e-13 8.526513e-14
[11] -2.842171e-14 -2.842171e-14 -8.526513e-14 8.526513e-14 1.136868e-13
[16] 1.136868e-13 -5.684342e-14 5.684342e-14 -5.684342e-14 -2.273737e-13
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
2 11
6 15
4 16
5 7
8 15
10 13
6 17
8 13
8 8
6 4
1 4
4 16
4 16
7 12
7 10
2 9
7 2
5 4
1 2
7 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] 2.434906
> Min(tmp)
[1] -3.019138
> mean(tmp)
[1] 0.0201035
> Sum(tmp)
[1] 2.01035
> Var(tmp)
[1] 1.106098
>
> rowMeans(tmp)
[1] 0.0201035
> rowSums(tmp)
[1] 2.01035
> rowVars(tmp)
[1] 1.106098
> rowSd(tmp)
[1] 1.051712
> rowMax(tmp)
[1] 2.434906
> rowMin(tmp)
[1] -3.019138
>
> colMeans(tmp)
[1] -0.061302974 -0.781344261 0.588254526 -0.578629084 -0.294903059
[6] -1.640753396 -0.099469153 0.179703158 0.292597096 1.110596026
[11] 0.038654873 1.227231050 1.564108129 0.065594523 0.369996152
[16] -0.485421348 -1.804948830 1.396547109 -0.001594486 0.532972974
[21] 1.229089499 -0.337294322 0.484052591 0.882448729 -0.373897317
[26] 2.205923286 0.040783864 0.443720868 0.742438276 1.214092631
[31] -1.708489410 -1.130895866 1.949223695 -0.437422577 0.874828442
[36] 1.972181091 0.118044926 -0.718233296 -1.306333021 -0.614809843
[41] 1.672036522 -1.207367389 -0.085159717 2.434906120 -0.048970051
[46] -0.585912093 0.587753757 -1.766716058 2.271601190 1.096892635
[51] -0.076980207 0.073996541 0.662539452 0.944730350 1.038686050
[56] -0.241034985 1.194450657 -1.207966769 -0.200282243 -0.681306765
[61] -1.306813513 0.007791649 0.130673423 0.070111881 0.244040096
[66] -0.979520436 0.969018154 0.577976542 -1.071309057 1.299595061
[71] -0.100019483 1.810929571 -0.824704138 0.955945732 0.935011887
[76] 0.107068740 0.577348981 -0.357756341 -1.248387066 -1.045736893
[81] -1.308203092 -1.305659472 -0.264692136 -0.897091890 -1.376503832
[86] 0.814632900 -0.458132721 -0.127002451 -3.019138408 -1.452857217
[91] 0.193507861 0.195833430 0.793622380 -0.111976466 -1.811904293
[96] -2.009608130 0.308623250 0.327301691 0.324500343 -0.579404403
> colSums(tmp)
[1] -0.061302974 -0.781344261 0.588254526 -0.578629084 -0.294903059
[6] -1.640753396 -0.099469153 0.179703158 0.292597096 1.110596026
[11] 0.038654873 1.227231050 1.564108129 0.065594523 0.369996152
[16] -0.485421348 -1.804948830 1.396547109 -0.001594486 0.532972974
[21] 1.229089499 -0.337294322 0.484052591 0.882448729 -0.373897317
[26] 2.205923286 0.040783864 0.443720868 0.742438276 1.214092631
[31] -1.708489410 -1.130895866 1.949223695 -0.437422577 0.874828442
[36] 1.972181091 0.118044926 -0.718233296 -1.306333021 -0.614809843
[41] 1.672036522 -1.207367389 -0.085159717 2.434906120 -0.048970051
[46] -0.585912093 0.587753757 -1.766716058 2.271601190 1.096892635
[51] -0.076980207 0.073996541 0.662539452 0.944730350 1.038686050
[56] -0.241034985 1.194450657 -1.207966769 -0.200282243 -0.681306765
[61] -1.306813513 0.007791649 0.130673423 0.070111881 0.244040096
[66] -0.979520436 0.969018154 0.577976542 -1.071309057 1.299595061
[71] -0.100019483 1.810929571 -0.824704138 0.955945732 0.935011887
[76] 0.107068740 0.577348981 -0.357756341 -1.248387066 -1.045736893
[81] -1.308203092 -1.305659472 -0.264692136 -0.897091890 -1.376503832
[86] 0.814632900 -0.458132721 -0.127002451 -3.019138408 -1.452857217
[91] 0.193507861 0.195833430 0.793622380 -0.111976466 -1.811904293
[96] -2.009608130 0.308623250 0.327301691 0.324500343 -0.579404403
> 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] -0.061302974 -0.781344261 0.588254526 -0.578629084 -0.294903059
[6] -1.640753396 -0.099469153 0.179703158 0.292597096 1.110596026
[11] 0.038654873 1.227231050 1.564108129 0.065594523 0.369996152
[16] -0.485421348 -1.804948830 1.396547109 -0.001594486 0.532972974
[21] 1.229089499 -0.337294322 0.484052591 0.882448729 -0.373897317
[26] 2.205923286 0.040783864 0.443720868 0.742438276 1.214092631
[31] -1.708489410 -1.130895866 1.949223695 -0.437422577 0.874828442
[36] 1.972181091 0.118044926 -0.718233296 -1.306333021 -0.614809843
[41] 1.672036522 -1.207367389 -0.085159717 2.434906120 -0.048970051
[46] -0.585912093 0.587753757 -1.766716058 2.271601190 1.096892635
[51] -0.076980207 0.073996541 0.662539452 0.944730350 1.038686050
[56] -0.241034985 1.194450657 -1.207966769 -0.200282243 -0.681306765
[61] -1.306813513 0.007791649 0.130673423 0.070111881 0.244040096
[66] -0.979520436 0.969018154 0.577976542 -1.071309057 1.299595061
[71] -0.100019483 1.810929571 -0.824704138 0.955945732 0.935011887
[76] 0.107068740 0.577348981 -0.357756341 -1.248387066 -1.045736893
[81] -1.308203092 -1.305659472 -0.264692136 -0.897091890 -1.376503832
[86] 0.814632900 -0.458132721 -0.127002451 -3.019138408 -1.452857217
[91] 0.193507861 0.195833430 0.793622380 -0.111976466 -1.811904293
[96] -2.009608130 0.308623250 0.327301691 0.324500343 -0.579404403
> colMin(tmp)
[1] -0.061302974 -0.781344261 0.588254526 -0.578629084 -0.294903059
[6] -1.640753396 -0.099469153 0.179703158 0.292597096 1.110596026
[11] 0.038654873 1.227231050 1.564108129 0.065594523 0.369996152
[16] -0.485421348 -1.804948830 1.396547109 -0.001594486 0.532972974
[21] 1.229089499 -0.337294322 0.484052591 0.882448729 -0.373897317
[26] 2.205923286 0.040783864 0.443720868 0.742438276 1.214092631
[31] -1.708489410 -1.130895866 1.949223695 -0.437422577 0.874828442
[36] 1.972181091 0.118044926 -0.718233296 -1.306333021 -0.614809843
[41] 1.672036522 -1.207367389 -0.085159717 2.434906120 -0.048970051
[46] -0.585912093 0.587753757 -1.766716058 2.271601190 1.096892635
[51] -0.076980207 0.073996541 0.662539452 0.944730350 1.038686050
[56] -0.241034985 1.194450657 -1.207966769 -0.200282243 -0.681306765
[61] -1.306813513 0.007791649 0.130673423 0.070111881 0.244040096
[66] -0.979520436 0.969018154 0.577976542 -1.071309057 1.299595061
[71] -0.100019483 1.810929571 -0.824704138 0.955945732 0.935011887
[76] 0.107068740 0.577348981 -0.357756341 -1.248387066 -1.045736893
[81] -1.308203092 -1.305659472 -0.264692136 -0.897091890 -1.376503832
[86] 0.814632900 -0.458132721 -0.127002451 -3.019138408 -1.452857217
[91] 0.193507861 0.195833430 0.793622380 -0.111976466 -1.811904293
[96] -2.009608130 0.308623250 0.327301691 0.324500343 -0.579404403
> colMedians(tmp)
[1] -0.061302974 -0.781344261 0.588254526 -0.578629084 -0.294903059
[6] -1.640753396 -0.099469153 0.179703158 0.292597096 1.110596026
[11] 0.038654873 1.227231050 1.564108129 0.065594523 0.369996152
[16] -0.485421348 -1.804948830 1.396547109 -0.001594486 0.532972974
[21] 1.229089499 -0.337294322 0.484052591 0.882448729 -0.373897317
[26] 2.205923286 0.040783864 0.443720868 0.742438276 1.214092631
[31] -1.708489410 -1.130895866 1.949223695 -0.437422577 0.874828442
[36] 1.972181091 0.118044926 -0.718233296 -1.306333021 -0.614809843
[41] 1.672036522 -1.207367389 -0.085159717 2.434906120 -0.048970051
[46] -0.585912093 0.587753757 -1.766716058 2.271601190 1.096892635
[51] -0.076980207 0.073996541 0.662539452 0.944730350 1.038686050
[56] -0.241034985 1.194450657 -1.207966769 -0.200282243 -0.681306765
[61] -1.306813513 0.007791649 0.130673423 0.070111881 0.244040096
[66] -0.979520436 0.969018154 0.577976542 -1.071309057 1.299595061
[71] -0.100019483 1.810929571 -0.824704138 0.955945732 0.935011887
[76] 0.107068740 0.577348981 -0.357756341 -1.248387066 -1.045736893
[81] -1.308203092 -1.305659472 -0.264692136 -0.897091890 -1.376503832
[86] 0.814632900 -0.458132721 -0.127002451 -3.019138408 -1.452857217
[91] 0.193507861 0.195833430 0.793622380 -0.111976466 -1.811904293
[96] -2.009608130 0.308623250 0.327301691 0.324500343 -0.579404403
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -0.06130297 -0.7813443 0.5882545 -0.5786291 -0.2949031 -1.640753
[2,] -0.06130297 -0.7813443 0.5882545 -0.5786291 -0.2949031 -1.640753
[,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] -0.09946915 0.1797032 0.2925971 1.110596 0.03865487 1.227231 1.564108
[2,] -0.09946915 0.1797032 0.2925971 1.110596 0.03865487 1.227231 1.564108
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 0.06559452 0.3699962 -0.4854213 -1.804949 1.396547 -0.001594486 0.532973
[2,] 0.06559452 0.3699962 -0.4854213 -1.804949 1.396547 -0.001594486 0.532973
[,21] [,22] [,23] [,24] [,25] [,26] [,27]
[1,] 1.229089 -0.3372943 0.4840526 0.8824487 -0.3738973 2.205923 0.04078386
[2,] 1.229089 -0.3372943 0.4840526 0.8824487 -0.3738973 2.205923 0.04078386
[,28] [,29] [,30] [,31] [,32] [,33] [,34]
[1,] 0.4437209 0.7424383 1.214093 -1.708489 -1.130896 1.949224 -0.4374226
[2,] 0.4437209 0.7424383 1.214093 -1.708489 -1.130896 1.949224 -0.4374226
[,35] [,36] [,37] [,38] [,39] [,40] [,41]
[1,] 0.8748284 1.972181 0.1180449 -0.7182333 -1.306333 -0.6148098 1.672037
[2,] 0.8748284 1.972181 0.1180449 -0.7182333 -1.306333 -0.6148098 1.672037
[,42] [,43] [,44] [,45] [,46] [,47] [,48]
[1,] -1.207367 -0.08515972 2.434906 -0.04897005 -0.5859121 0.5877538 -1.766716
[2,] -1.207367 -0.08515972 2.434906 -0.04897005 -0.5859121 0.5877538 -1.766716
[,49] [,50] [,51] [,52] [,53] [,54] [,55]
[1,] 2.271601 1.096893 -0.07698021 0.07399654 0.6625395 0.9447304 1.038686
[2,] 2.271601 1.096893 -0.07698021 0.07399654 0.6625395 0.9447304 1.038686
[,56] [,57] [,58] [,59] [,60] [,61] [,62]
[1,] -0.241035 1.194451 -1.207967 -0.2002822 -0.6813068 -1.306814 0.007791649
[2,] -0.241035 1.194451 -1.207967 -0.2002822 -0.6813068 -1.306814 0.007791649
[,63] [,64] [,65] [,66] [,67] [,68] [,69]
[1,] 0.1306734 0.07011188 0.2440401 -0.9795204 0.9690182 0.5779765 -1.071309
[2,] 0.1306734 0.07011188 0.2440401 -0.9795204 0.9690182 0.5779765 -1.071309
[,70] [,71] [,72] [,73] [,74] [,75] [,76]
[1,] 1.299595 -0.1000195 1.81093 -0.8247041 0.9559457 0.9350119 0.1070687
[2,] 1.299595 -0.1000195 1.81093 -0.8247041 0.9559457 0.9350119 0.1070687
[,77] [,78] [,79] [,80] [,81] [,82] [,83]
[1,] 0.577349 -0.3577563 -1.248387 -1.045737 -1.308203 -1.305659 -0.2646921
[2,] 0.577349 -0.3577563 -1.248387 -1.045737 -1.308203 -1.305659 -0.2646921
[,84] [,85] [,86] [,87] [,88] [,89] [,90]
[1,] -0.8970919 -1.376504 0.8146329 -0.4581327 -0.1270025 -3.019138 -1.452857
[2,] -0.8970919 -1.376504 0.8146329 -0.4581327 -0.1270025 -3.019138 -1.452857
[,91] [,92] [,93] [,94] [,95] [,96] [,97]
[1,] 0.1935079 0.1958334 0.7936224 -0.1119765 -1.811904 -2.009608 0.3086232
[2,] 0.1935079 0.1958334 0.7936224 -0.1119765 -1.811904 -2.009608 0.3086232
[,98] [,99] [,100]
[1,] 0.3273017 0.3245003 -0.5794044
[2,] 0.3273017 0.3245003 -0.5794044
>
>
> Max(tmp2)
[1] 3.056873
> Min(tmp2)
[1] -1.96935
> mean(tmp2)
[1] -0.1684881
> Sum(tmp2)
[1] -16.84881
> Var(tmp2)
[1] 0.9073726
>
> rowMeans(tmp2)
[1] -0.635655763 0.042681220 -1.798185236 -0.929705704 -1.305554036
[6] -0.501741428 -0.499706642 -1.266138869 -1.969350473 2.739840921
[11] -0.737439700 0.082668462 -0.474981128 -0.086946873 1.222068861
[16] 0.483264730 0.281642000 -1.017480964 -0.175770619 -1.295870073
[21] 1.325655097 0.211499713 -0.045018648 -0.175860829 -1.500245110
[26] 0.132117722 3.056872633 -0.191079014 -1.633610122 -1.022293075
[31] -0.983670154 0.137986893 -0.018017646 -0.712619919 0.045413708
[36] -0.491021038 0.540193249 -0.071423861 1.207173070 -1.115458396
[41] -1.662407482 0.488186077 -0.325649250 0.036396456 -0.010187965
[46] 1.052102794 0.053176151 -1.433764254 -0.999374503 0.940556650
[51] -1.036105939 -0.668809263 0.301702628 0.041952019 0.203698482
[56] 0.582436717 -1.687873400 -0.547771643 1.548341358 0.698644278
[61] -1.520205005 -1.095587221 -0.571902367 -1.606914210 0.374751066
[66] -0.522886428 -0.360541376 0.319626623 0.996351903 -0.022214170
[71] 0.070645519 -0.167392245 -0.621295227 -0.281721018 0.715431062
[76] 0.922566120 -1.043065581 -1.521346257 0.065864438 -0.126284990
[81] 0.043539783 -0.597810510 -1.055394702 1.224284089 0.313552634
[86] -0.990580011 -0.323561387 -1.450735766 0.088760761 -0.868788369
[91] 0.335748937 -0.011132869 1.895680589 -0.907784158 -0.527983682
[96] 0.058251140 0.951054740 0.957024225 1.585369176 -0.001664174
> rowSums(tmp2)
[1] -0.635655763 0.042681220 -1.798185236 -0.929705704 -1.305554036
[6] -0.501741428 -0.499706642 -1.266138869 -1.969350473 2.739840921
[11] -0.737439700 0.082668462 -0.474981128 -0.086946873 1.222068861
[16] 0.483264730 0.281642000 -1.017480964 -0.175770619 -1.295870073
[21] 1.325655097 0.211499713 -0.045018648 -0.175860829 -1.500245110
[26] 0.132117722 3.056872633 -0.191079014 -1.633610122 -1.022293075
[31] -0.983670154 0.137986893 -0.018017646 -0.712619919 0.045413708
[36] -0.491021038 0.540193249 -0.071423861 1.207173070 -1.115458396
[41] -1.662407482 0.488186077 -0.325649250 0.036396456 -0.010187965
[46] 1.052102794 0.053176151 -1.433764254 -0.999374503 0.940556650
[51] -1.036105939 -0.668809263 0.301702628 0.041952019 0.203698482
[56] 0.582436717 -1.687873400 -0.547771643 1.548341358 0.698644278
[61] -1.520205005 -1.095587221 -0.571902367 -1.606914210 0.374751066
[66] -0.522886428 -0.360541376 0.319626623 0.996351903 -0.022214170
[71] 0.070645519 -0.167392245 -0.621295227 -0.281721018 0.715431062
[76] 0.922566120 -1.043065581 -1.521346257 0.065864438 -0.126284990
[81] 0.043539783 -0.597810510 -1.055394702 1.224284089 0.313552634
[86] -0.990580011 -0.323561387 -1.450735766 0.088760761 -0.868788369
[91] 0.335748937 -0.011132869 1.895680589 -0.907784158 -0.527983682
[96] 0.058251140 0.951054740 0.957024225 1.585369176 -0.001664174
> 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] -0.635655763 0.042681220 -1.798185236 -0.929705704 -1.305554036
[6] -0.501741428 -0.499706642 -1.266138869 -1.969350473 2.739840921
[11] -0.737439700 0.082668462 -0.474981128 -0.086946873 1.222068861
[16] 0.483264730 0.281642000 -1.017480964 -0.175770619 -1.295870073
[21] 1.325655097 0.211499713 -0.045018648 -0.175860829 -1.500245110
[26] 0.132117722 3.056872633 -0.191079014 -1.633610122 -1.022293075
[31] -0.983670154 0.137986893 -0.018017646 -0.712619919 0.045413708
[36] -0.491021038 0.540193249 -0.071423861 1.207173070 -1.115458396
[41] -1.662407482 0.488186077 -0.325649250 0.036396456 -0.010187965
[46] 1.052102794 0.053176151 -1.433764254 -0.999374503 0.940556650
[51] -1.036105939 -0.668809263 0.301702628 0.041952019 0.203698482
[56] 0.582436717 -1.687873400 -0.547771643 1.548341358 0.698644278
[61] -1.520205005 -1.095587221 -0.571902367 -1.606914210 0.374751066
[66] -0.522886428 -0.360541376 0.319626623 0.996351903 -0.022214170
[71] 0.070645519 -0.167392245 -0.621295227 -0.281721018 0.715431062
[76] 0.922566120 -1.043065581 -1.521346257 0.065864438 -0.126284990
[81] 0.043539783 -0.597810510 -1.055394702 1.224284089 0.313552634
[86] -0.990580011 -0.323561387 -1.450735766 0.088760761 -0.868788369
[91] 0.335748937 -0.011132869 1.895680589 -0.907784158 -0.527983682
[96] 0.058251140 0.951054740 0.957024225 1.585369176 -0.001664174
> rowMin(tmp2)
[1] -0.635655763 0.042681220 -1.798185236 -0.929705704 -1.305554036
[6] -0.501741428 -0.499706642 -1.266138869 -1.969350473 2.739840921
[11] -0.737439700 0.082668462 -0.474981128 -0.086946873 1.222068861
[16] 0.483264730 0.281642000 -1.017480964 -0.175770619 -1.295870073
[21] 1.325655097 0.211499713 -0.045018648 -0.175860829 -1.500245110
[26] 0.132117722 3.056872633 -0.191079014 -1.633610122 -1.022293075
[31] -0.983670154 0.137986893 -0.018017646 -0.712619919 0.045413708
[36] -0.491021038 0.540193249 -0.071423861 1.207173070 -1.115458396
[41] -1.662407482 0.488186077 -0.325649250 0.036396456 -0.010187965
[46] 1.052102794 0.053176151 -1.433764254 -0.999374503 0.940556650
[51] -1.036105939 -0.668809263 0.301702628 0.041952019 0.203698482
[56] 0.582436717 -1.687873400 -0.547771643 1.548341358 0.698644278
[61] -1.520205005 -1.095587221 -0.571902367 -1.606914210 0.374751066
[66] -0.522886428 -0.360541376 0.319626623 0.996351903 -0.022214170
[71] 0.070645519 -0.167392245 -0.621295227 -0.281721018 0.715431062
[76] 0.922566120 -1.043065581 -1.521346257 0.065864438 -0.126284990
[81] 0.043539783 -0.597810510 -1.055394702 1.224284089 0.313552634
[86] -0.990580011 -0.323561387 -1.450735766 0.088760761 -0.868788369
[91] 0.335748937 -0.011132869 1.895680589 -0.907784158 -0.527983682
[96] 0.058251140 0.951054740 0.957024225 1.585369176 -0.001664174
>
> colMeans(tmp2)
[1] -0.1684881
> colSums(tmp2)
[1] -16.84881
> colVars(tmp2)
[1] 0.9073726
> colSd(tmp2)
[1] 0.9525611
> colMax(tmp2)
[1] 3.056873
> colMin(tmp2)
[1] -1.96935
> colMedians(tmp2)
[1] -0.1066159
> colRanges(tmp2)
[,1]
[1,] -1.969350
[2,] 3.056873
>
> 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] -5.219142 -2.471906 1.760490 -3.273434 -6.027397 3.349625 -2.286177
[8] -2.637590 -3.754205 -4.633749
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.64585684
[2,] -0.99915713
[3,] -0.58537630
[4,] -0.07683203
[5,] 0.99174873
>
> rowApply(tmp,sum)
[1] 0.3603470 -7.7052274 -1.0570303 0.1356095 2.6925185 0.3421963
[7] -3.2369474 -5.6943222 -8.5707810 -2.4598496
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 3 9 8 4 1 2 7 7 2 1
[2,] 2 6 6 5 6 8 5 2 5 10
[3,] 7 10 2 9 9 7 6 8 7 8
[4,] 1 4 7 8 7 1 8 5 4 5
[5,] 10 7 1 2 3 3 2 4 9 2
[6,] 6 8 9 10 8 9 9 1 8 7
[7,] 4 1 5 6 5 10 1 10 10 3
[8,] 8 3 4 3 4 6 10 9 6 4
[9,] 5 2 3 7 10 4 3 6 3 6
[10,] 9 5 10 1 2 5 4 3 1 9
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 1.4307785 2.2812357 -1.4989281 1.0682766 -0.4175877 -0.6251746
[7] -1.2792156 -1.6684723 -3.2747447 1.2819196 -1.8197586 -0.7829300
[13] -1.7502629 -0.1657341 -4.9881010 -0.2795653 -0.4437590 -1.9512493
[19] -0.9017444 -0.4899375
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.32558676
[2,] -0.25670826
[3,] -0.08344346
[4,] 0.73891406
[5,] 1.35760293
>
> rowApply(tmp,sum)
[1] -3.4455899 -4.7910440 -3.7223507 -0.9058824 -3.4100878
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 20 14 15 10 10
[2,] 16 20 13 15 5
[3,] 17 13 3 14 6
[4,] 8 12 20 20 1
[5,] 12 3 14 7 19
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 1.35760293 0.6782175 0.6818844 -0.6336489 -0.03217306 0.418821314
[2,] -0.08344346 1.6843335 -0.1410173 -0.2033160 -1.41464373 0.372468913
[3,] 0.73891406 0.3215636 -1.4295844 1.2632551 0.49563070 -0.235803138
[4,] -0.25670826 0.7572645 0.5147239 2.1235499 -0.75739361 -0.001175775
[5,] -0.32558676 -1.1601435 -1.1249347 -1.4815636 1.29099205 -1.179485864
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.3221900 -0.06833163 -1.2740726 -0.1297442 -0.20585787 1.1474099
[2,] 1.1041248 -0.29817175 0.1610981 -1.1026698 -0.96563261 -0.8166964
[3,] -1.5035106 -2.43513655 -0.5398733 1.1091233 0.77941989 -0.6936170
[4,] -0.6050101 -0.32363135 -1.0372053 0.7982298 -1.46935268 -1.0880006
[5,] -0.5970097 1.45679893 -0.5846917 0.6069805 0.04166468 0.6679741
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.8732164 -2.0367011 -0.7892374 0.2069750 1.3436952 -1.1830086
[2,] -0.3925085 1.4591872 -0.8413885 -1.5956495 1.2995547 -0.5370721
[3,] -1.2882876 0.9307117 -0.3602630 1.0638841 -0.9008694 -0.9733995
[4,] 0.3662990 -1.0309391 -1.5670332 0.8175743 -0.9336856 0.1144399
[5,] 0.4374507 0.5120071 -1.4301789 -0.7723491 -1.2524539 0.6277911
[,19] [,20]
[1,] -0.7264093 -1.6499852
[2,] -1.4867924 -0.9928091
[3,] 0.2706115 -0.3351201
[4,] 1.2442180 1.4279540
[5,] -0.2033722 1.0600229
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /home/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: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 654 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 564 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 480 bytes.
>
>
> rm(tmp)
>
>
> ###
> ### Testing colnames and rownames
> ###
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
>
>
> colnames(tmp)
NULL
> rownames(tmp)
NULL
>
>
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
> colnames(tmp)
[1] "col1" "col2" "col3" "col4" "col5" "col6" "col7" "col8" "col9"
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
>
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7
row1 -1.158496 -1.005852 0.02004561 -0.5922405 -0.5700888 -0.7311548 -0.1535277
col8 col9 col10 col11 col12 col13 col14
row1 0.01240561 0.7359256 -0.6048394 -0.3932125 -0.4386314 1.587639 -0.8667347
col15 col16 col17 col18 col19 col20
row1 0.8452362 1.398396 1.195164 1.292579 -0.1921184 0.6825519
> tmp[,"col10"]
col10
row1 -0.6048394
row2 1.8933846
row3 -0.4207072
row4 0.1279097
row5 -0.2088059
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 -1.158496 -1.0058523 0.02004561 -0.5922405 -0.5700888 -0.7311548
row5 -1.315140 -0.2661128 1.47065630 1.7470481 2.4425618 -1.0064577
col7 col8 col9 col10 col11 col12 col13
row1 -0.1535277 0.01240561 0.7359256 -0.6048394 -0.3932125 -0.4386314 1.587639
row5 -1.0816342 0.35065449 -1.4558539 -0.2088059 0.4658908 0.2678983 1.416689
col14 col15 col16 col17 col18 col19 col20
row1 -0.8667347 0.8452362 1.3983955 1.1951643 1.2925792 -0.1921184 0.6825519
row5 -0.2232446 -0.6909793 0.3533953 0.4727225 0.2953723 -1.3826497 0.3379500
> tmp[,c("col6","col20")]
col6 col20
row1 -0.73115480 0.6825519
row2 -0.04855142 -0.9206290
row3 -0.67456993 -1.0043782
row4 -0.15585273 -1.1024783
row5 -1.00645769 0.3379500
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.7311548 0.6825519
row5 -1.0064577 0.3379500
>
>
>
>
> 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 48.866 49.45581 50.16218 50.56652 50.69791 105.5616 48.80575 50.52647
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.41538 49.86678 51.05572 51.81418 50.23561 50.00231 50.60648 50.52046
col17 col18 col19 col20
row1 49.56297 49.71425 50.52953 104.226
> tmp[,"col10"]
col10
row1 49.86678
row2 30.64079
row3 31.23554
row4 29.90842
row5 49.68383
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 48.86600 49.45581 50.16218 50.56652 50.69791 105.5616 48.80575 50.52647
row5 49.08637 51.19422 50.59122 49.09991 50.11247 105.1761 50.24550 50.35220
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.41538 49.86678 51.05572 51.81418 50.23561 50.00231 50.60648 50.52046
row5 49.56607 49.68383 50.62171 50.26745 47.83696 51.51442 50.43602 51.52114
col17 col18 col19 col20
row1 49.56297 49.71425 50.52953 104.226
row5 50.10156 50.61419 49.27142 103.434
> tmp[,c("col6","col20")]
col6 col20
row1 105.56165 104.22604
row2 76.21619 73.96348
row3 75.66159 75.84136
row4 74.53363 73.28154
row5 105.17608 103.43402
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.5616 104.226
row5 105.1761 103.434
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.5616 104.226
row5 105.1761 103.434
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -0.9055056
[2,] -1.0179759
[3,] -1.8379796
[4,] -1.2207159
[5,] 0.1594340
> tmp[,c("col17","col7")]
col17 col7
[1,] 1.00937304 -0.1698601
[2,] -0.91174728 0.2909300
[3,] -0.08156446 0.7907662
[4,] 0.29749362 -1.7891461
[5,] -0.10328648 -0.9442885
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.02636831 0.9457825
[2,] 3.53343685 -0.7396442
[3,] 2.80812623 -0.1697623
[4,] 0.11430980 -0.3985627
[5,] -0.80511231 1.1336480
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.02636831
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.02636831
[2,] 3.53343685
>
>
>
> 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 -0.3315647 -0.7302665 0.03670421 0.3832400 -1.163813 0.5973715 -0.9439597
row1 -0.4329656 0.9908705 1.09398692 0.3406831 0.117316 -1.0521894 -0.1551609
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row3 0.4575223 -1.945104 -0.09544851 1.623853 0.4169268 -1.789613 0.6044078
row1 -0.2723546 -1.002342 -0.11752076 1.247555 -0.4926320 -1.295398 0.2576084
[,15] [,16] [,17] [,18] [,19] [,20]
row3 -0.9938799 0.3423694 0.1754527 -0.7361531 0.9905513 1.998188
row1 1.2606260 0.2691382 -0.3901188 -2.0970617 -0.3188014 -1.382292
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 1.273644 -1.355544 0.1672424 0.2312206 0.3730965 0.2450922 -1.25215
[,8] [,9] [,10]
row2 -1.99766 2.110799 0.7580616
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -0.1169278 1.487027 -1.54883 0.4931968 -0.4788949 0.7336074 0.6365377
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.5524715 0.8560842 1.210674 -1.152749 0.69072 1.439479 -1.822884
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.884344 1.126785 0.06604708 0.7390954 -0.3631645 0.7607908
>
>
> 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: 0x3fee2c00>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM31525f11612b0e"
[2] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM31525f4861b9c7"
[3] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM31525f6725c7c7"
[4] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM31525f2dcb4c1b"
[5] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM31525f2ede3fd5"
[6] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM31525f390bc39c"
[7] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM31525f52aab995"
[8] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM31525f2ebee9a3"
[9] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM31525f5868f46e"
[10] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM31525f58d4067a"
[11] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM31525f1732b691"
[12] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM31525f532b86d5"
[13] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM31525f663f4efa"
[14] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM31525f712f4c33"
[15] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM31525f402bc2c6"
>
>
> ### 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: 0x3d705e50>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x3d705e50>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x3d705e50>
> rowMedians(tmp)
[1] -0.237131404 0.282798112 0.279834992 0.096498894 0.039514263
[6] -0.047050894 -0.059429211 -0.109953623 -0.104555021 0.530656450
[11] 0.100791797 0.570295718 -0.355355816 -0.265278376 0.067425783
[16] 0.419123627 0.277065926 -0.242089539 0.377535541 0.222202439
[21] 0.754662746 0.061693617 0.276241957 -0.273043806 -0.441040141
[26] 0.500494108 -0.122328601 -0.034762323 0.230224102 0.025549402
[31] -0.086055534 -0.478469540 -0.037190080 -0.692513095 0.270742970
[36] 0.397909531 0.334954465 0.109439793 0.459763833 -0.248024952
[41] 0.883292816 0.255347261 0.654101620 -0.247367913 -0.535045494
[46] 0.339403208 -0.205695811 0.015853899 0.104966403 0.047154021
[51] 0.026646558 0.405623772 0.500054230 0.257577471 -0.443809909
[56] 0.027369828 0.238332575 0.217017321 0.032699258 0.293263169
[61] 0.080321100 -0.086202814 0.384125938 -0.265340745 -0.662831590
[66] 0.320533629 0.086438044 -0.150655737 0.248541606 -0.558059768
[71] 0.033378250 -0.286759199 -0.239292680 0.152764101 -0.040570957
[76] 0.496554607 -0.481820363 0.290776717 -0.007260041 -0.200571458
[81] -0.015210286 0.338171233 -0.068275734 -0.554229296 -0.195165351
[86] 0.544558302 0.239293523 0.014516355 0.269855799 0.100175499
[91] 0.076767222 0.161910448 -0.418959395 -0.149819640 -0.176905404
[96] -0.302358022 -0.365350726 0.186315646 -0.150572118 -0.132112357
[101] 0.149234955 -0.264274050 -0.321332174 -0.154767786 0.217464478
[106] 0.008583891 -0.263021227 -0.175752886 0.168784792 -0.206309016
[111] -0.201277247 0.506448190 -0.191414056 -0.727714711 -0.057679883
[116] 0.255259034 -0.354787645 -0.116365381 -0.222438405 -0.334507574
[121] -0.362057858 -0.029147198 -0.399200198 -0.497446590 0.344839639
[126] 0.179761874 0.364995214 -0.418863182 -0.066775899 -0.239312540
[131] -0.186740665 -0.145737881 -0.109855650 -0.394841306 0.212499198
[136] -0.042186349 0.235183041 -0.152947695 -0.475126930 0.008029912
[141] -0.244178721 -0.042440973 0.181486525 0.696713226 0.380554453
[146] 0.327093103 -0.299694537 -0.332331000 -0.542102741 0.010053113
[151] 0.229746378 -0.017695852 -0.622516426 -0.369844318 0.725319267
[156] -0.119654945 -0.282019724 -0.013961941 -0.467003490 0.258388757
[161] -0.133682059 0.147031464 0.201817711 0.809066326 0.181670764
[166] -0.200041447 0.043300812 0.369357228 -0.639170981 -0.816788910
[171] 0.173622068 0.453825404 -0.036213710 0.055884323 -0.229631017
[176] -0.660545604 0.027614448 0.349195539 0.153745712 -0.372149491
[181] 0.023575094 -0.485875224 -0.668272797 -0.227910559 0.384797616
[186] 0.189059397 0.106560599 -0.429824833 -0.502791070 -0.203682776
[191] 0.116497119 0.217798177 -0.098821254 0.015107818 0.231228406
[196] 0.267032122 0.436758891 0.115362519 -0.093645383 0.253735686
[201] -0.073894977 0.160138072 -0.485986464 0.197467674 -0.052642305
[206] 0.301633533 -0.514557823 -0.292896417 -0.281956433 0.444398697
[211] -0.254305618 -0.074321940 -0.041510884 0.022039489 -0.186984392
[216] 0.247857791 0.377562209 0.097163233 0.361543799 0.579964370
[221] 0.289975530 -0.234613628 -0.020593450 0.439904239 -0.177168275
[226] 0.647477074 0.257166275 -0.515788734 0.644893057 -0.302774193
>
> proc.time()
user system elapsed
1.905 0.860 2.802
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.5.0 (2025-04-11) -- "How About a Twenty-Six"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu
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: 0x38e6eff0>
> .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: 0x38e6eff0>
> .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: 0x38e6eff0>
> .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: 0x38e6eff0>
> 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: 0x38d79470>
> .Call("R_bm_AddColumn",P)
<pointer: 0x38d79470>
> .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: 0x38d79470>
> .Call("R_bm_AddColumn",P)
<pointer: 0x38d79470>
> .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: 0x38d79470>
> 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: 0x38d540e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x38d540e0>
> .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: 0x38d540e0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x38d540e0>
> .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: 0x38d540e0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x38d540e0>
> .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: 0x38d540e0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x38d540e0>
> .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: 0x38d540e0>
> 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: 0x37cdb520>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x37cdb520>
> .Call("R_bm_AddColumn",P)
<pointer: 0x37cdb520>
> .Call("R_bm_AddColumn",P)
<pointer: 0x37cdb520>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile31530c31ad1fd7" "BufferedMatrixFile31530c4f65369f"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile31530c31ad1fd7" "BufferedMatrixFile31530c4f65369f"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x39c24030>
> .Call("R_bm_AddColumn",P)
<pointer: 0x39c24030>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x39c24030>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x39c24030>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x39c24030>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x39c24030>
> .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: 0x385ef5c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x385ef5c0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x385ef5c0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x385ef5c0>
> 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: 0x396cff30>
> .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: 0x396cff30>
> rm(P)
>
> proc.time()
user system elapsed
0.311 0.056 0.354
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.5.0 (2025-04-11) -- "How About a Twenty-Six"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu
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
0.327 0.042 0.354