Ben Bolstad
| Snapshot Date: 2025-10-23 14:17 -0400 (Thu, 23 Oct 2025) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: devel |
| git_last_commit: 0147962 |
| git_last_commit_date: 2025-04-15 09:39:39 -0400 (Tue, 15 Apr 2025) |
| Back to Multiple platform build/check report for BioC 3.22: simplified long |
|
This page was generated on 2025-10-24 12:07 -0400 (Fri, 24 Oct 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 24.04.3 LTS) | x86_64 | 4.5.1 Patched (2025-08-23 r88802) -- "Great Square Root" | 4898 |
| lconway | macOS 12.7.6 Monterey | x86_64 | 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root" | 4688 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root" | 4634 |
| taishan | Linux (openEuler 24.03 LTS) | aarch64 | 4.5.0 (2025-04-11) -- "How About a Twenty-Six" | 4658 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
| Package 257/2359 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.73.0 (landing page) Ben Bolstad
| nebbiolo2 | Linux (Ubuntu 24.04.3 LTS) / x86_64 | OK | OK | OK | | ||||||||
| lconway | macOS 12.7.6 Monterey / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| kjohnson3 | macOS 13.7.7 Ventura / arm64 | OK | OK | WARNINGS | OK | | ||||||||
| taishan | Linux (openEuler 24.03 LTS) / aarch64 | OK | OK | OK | ||||||||||
|
To the developers/maintainers of the BufferedMatrix package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/BufferedMatrix.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. - 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: 2025-10-21 06:05:08 -0000 (Tue, 21 Oct 2025) |
| EndedAt: 2025-10-21 06:05:32 -0000 (Tue, 21 Oct 2025) |
| EllapsedTime: 24.0 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
0.317 0.056 0.357
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 Oct 21 06:05:25 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 Oct 21 06:05:25 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: 0x13dffff0>
>
>
>
> 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 Oct 21 06:05:26 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 Oct 21 06:05:26 2025"
>
> ColMode(tmp2)
<pointer: 0x13dffff0>
>
>
>
> ### 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,] 100.2621801 -1.96964186 -0.446484829 1.7822020
[2,] -0.8060205 0.04879804 -0.161963213 0.4266251
[3,] 0.1664961 0.41188956 -0.005142313 0.3233673
[4,] -0.3815489 -1.25669369 -0.148118670 -1.5344050
> 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,] 100.2621801 1.96964186 0.446484829 1.7822020
[2,] 0.8060205 0.04879804 0.161963213 0.4266251
[3,] 0.1664961 0.41188956 0.005142313 0.3233673
[4,] 0.3815489 1.25669369 0.148118670 1.5344050
> 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,] 10.0131004 1.4034393 0.66819520 1.3349914
[2,] 0.8977865 0.2209028 0.40244653 0.6531654
[3,] 0.4080394 0.6417862 0.07170993 0.5686539
[4,] 0.6176965 1.1210235 0.38486188 1.2387110
>
> 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,] 225.39318 41.00403 32.12844 40.13212
[2,] 34.78389 27.25783 29.18643 31.95828
[3,] 29.24689 31.82975 25.72224 31.00991
[4,] 31.55851 37.46693 28.99674 38.92152
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x1502f9a0>
> exp(tmp5)
<pointer: 0x1502f9a0>
> log(tmp5,2)
<pointer: 0x1502f9a0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 469.1264
> Min(tmp5)
[1] 52.23236
> mean(tmp5)
[1] 72.39885
> Sum(tmp5)
[1] 14479.77
> Var(tmp5)
[1] 877.191
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 90.18359 70.13793 67.52863 70.38377 69.88005 74.29987 67.20029 70.18944
[9] 70.55374 73.63113
> rowSums(tmp5)
[1] 1803.672 1402.759 1350.573 1407.675 1397.601 1485.997 1344.006 1403.789
[9] 1411.075 1472.623
> rowVars(tmp5)
[1] 8061.78996 105.50746 47.27068 81.74993 86.21162 69.35622
[7] 83.25774 77.65596 89.57595 68.22925
> rowSd(tmp5)
[1] 89.787471 10.271683 6.875368 9.041567 9.285021 8.328038 9.124568
[8] 8.812262 9.464457 8.260100
> rowMax(tmp5)
[1] 469.12638 85.57203 84.98060 85.55394 86.82726 93.64524 85.92703
[8] 85.00463 83.70119 87.37565
> rowMin(tmp5)
[1] 53.32256 53.98576 53.53748 52.23236 56.88987 59.29628 53.78289 53.45730
[9] 56.38080 61.34462
>
> colMeans(tmp5)
[1] 107.71746 68.11065 67.11373 71.35260 79.10175 67.76151 68.83481
[8] 68.47435 71.45815 63.98281 75.16354 73.66040 65.95520 71.32020
[15] 70.57007 70.38890 74.22106 70.82501 68.79559 73.16911
> colSums(tmp5)
[1] 1077.1746 681.1065 671.1373 713.5260 791.0175 677.6151 688.3481
[8] 684.7435 714.5815 639.8281 751.6354 736.6040 659.5520 713.2020
[15] 705.7007 703.8890 742.2106 708.2501 687.9559 731.6911
> colVars(tmp5)
[1] 16144.85476 104.59355 61.56258 110.19870 96.82526 71.66599
[7] 100.35613 38.61612 90.53300 64.17449 62.58516 50.46765
[13] 128.14323 75.26408 121.22189 34.98207 107.36963 98.74334
[19] 56.81817 65.85846
> colSd(tmp5)
[1] 127.062405 10.227099 7.846183 10.497557 9.839983 8.465577
[7] 10.017791 6.214187 9.514883 8.010898 7.911078 7.104058
[13] 11.320037 8.675487 11.010081 5.914564 10.361932 9.936968
[19] 7.537783 8.115323
> colMax(tmp5)
[1] 469.12638 85.34453 78.23123 85.96297 91.94425 82.12094 83.91608
[8] 76.08333 85.55394 79.91668 87.37565 81.50387 83.70119 86.82726
[15] 85.57203 81.89936 87.28076 93.64524 81.41760 80.78970
> colMin(tmp5)
[1] 60.87357 53.78289 53.53748 56.38080 58.44905 58.07376 53.32256 58.15722
[9] 57.71910 53.98576 64.03788 56.88987 52.23236 59.29628 53.45730 64.66739
[17] 61.50715 57.95994 58.57619 59.88072
>
>
> ### setting a random element to NA and then testing with na.rm=TRUE or na.rm=FALSE (The default)
>
>
> which.row <- sample(1:10,1,replace=TRUE)
> which.col <- sample(1:20,1,replace=TRUE)
>
> tmp5[which.row,which.col] <- NA
>
> Max(tmp5)
[1] NA
> Min(tmp5)
[1] NA
> mean(tmp5)
[1] NA
> Sum(tmp5)
[1] NA
> Var(tmp5)
[1] NA
>
> rowMeans(tmp5)
[1] 90.18359 70.13793 67.52863 70.38377 69.88005 74.29987 67.20029 70.18944
[9] 70.55374 NA
> rowSums(tmp5)
[1] 1803.672 1402.759 1350.573 1407.675 1397.601 1485.997 1344.006 1403.789
[9] 1411.075 NA
> rowVars(tmp5)
[1] 8061.78996 105.50746 47.27068 81.74993 86.21162 69.35622
[7] 83.25774 77.65596 89.57595 70.47053
> rowSd(tmp5)
[1] 89.787471 10.271683 6.875368 9.041567 9.285021 8.328038 9.124568
[8] 8.812262 9.464457 8.394672
> rowMax(tmp5)
[1] 469.12638 85.57203 84.98060 85.55394 86.82726 93.64524 85.92703
[8] 85.00463 83.70119 NA
> rowMin(tmp5)
[1] 53.32256 53.98576 53.53748 52.23236 56.88987 59.29628 53.78289 53.45730
[9] 56.38080 NA
>
> colMeans(tmp5)
[1] 107.71746 68.11065 67.11373 71.35260 79.10175 67.76151 68.83481
[8] 68.47435 71.45815 63.98281 75.16354 73.66040 NA 71.32020
[15] 70.57007 70.38890 74.22106 70.82501 68.79559 73.16911
> colSums(tmp5)
[1] 1077.1746 681.1065 671.1373 713.5260 791.0175 677.6151 688.3481
[8] 684.7435 714.5815 639.8281 751.6354 736.6040 NA 713.2020
[15] 705.7007 703.8890 742.2106 708.2501 687.9559 731.6911
> colVars(tmp5)
[1] 16144.85476 104.59355 61.56258 110.19870 96.82526 71.66599
[7] 100.35613 38.61612 90.53300 64.17449 62.58516 50.46765
[13] NA 75.26408 121.22189 34.98207 107.36963 98.74334
[19] 56.81817 65.85846
> colSd(tmp5)
[1] 127.062405 10.227099 7.846183 10.497557 9.839983 8.465577
[7] 10.017791 6.214187 9.514883 8.010898 7.911078 7.104058
[13] NA 8.675487 11.010081 5.914564 10.361932 9.936968
[19] 7.537783 8.115323
> colMax(tmp5)
[1] 469.12638 85.34453 78.23123 85.96297 91.94425 82.12094 83.91608
[8] 76.08333 85.55394 79.91668 87.37565 81.50387 NA 86.82726
[15] 85.57203 81.89936 87.28076 93.64524 81.41760 80.78970
> colMin(tmp5)
[1] 60.87357 53.78289 53.53748 56.38080 58.44905 58.07376 53.32256 58.15722
[9] 57.71910 53.98576 64.03788 56.88987 NA 59.29628 53.45730 64.66739
[17] 61.50715 57.95994 58.57619 59.88072
>
> Max(tmp5,na.rm=TRUE)
[1] 469.1264
> Min(tmp5,na.rm=TRUE)
[1] 52.23236
> mean(tmp5,na.rm=TRUE)
[1] 72.36679
> Sum(tmp5,na.rm=TRUE)
[1] 14400.99
> Var(tmp5,na.rm=TRUE)
[1] 881.4147
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.18359 70.13793 67.52863 70.38377 69.88005 74.29987 67.20029 70.18944
[9] 70.55374 73.36023
> rowSums(tmp5,na.rm=TRUE)
[1] 1803.672 1402.759 1350.573 1407.675 1397.601 1485.997 1344.006 1403.789
[9] 1411.075 1393.844
> rowVars(tmp5,na.rm=TRUE)
[1] 8061.78996 105.50746 47.27068 81.74993 86.21162 69.35622
[7] 83.25774 77.65596 89.57595 70.47053
> rowSd(tmp5,na.rm=TRUE)
[1] 89.787471 10.271683 6.875368 9.041567 9.285021 8.328038 9.124568
[8] 8.812262 9.464457 8.394672
> rowMax(tmp5,na.rm=TRUE)
[1] 469.12638 85.57203 84.98060 85.55394 86.82726 93.64524 85.92703
[8] 85.00463 83.70119 87.37565
> rowMin(tmp5,na.rm=TRUE)
[1] 53.32256 53.98576 53.53748 52.23236 56.88987 59.29628 53.78289 53.45730
[9] 56.38080 61.34462
>
> colMeans(tmp5,na.rm=TRUE)
[1] 107.71746 68.11065 67.11373 71.35260 79.10175 67.76151 68.83481
[8] 68.47435 71.45815 63.98281 75.16354 73.66040 64.53043 71.32020
[15] 70.57007 70.38890 74.22106 70.82501 68.79559 73.16911
> colSums(tmp5,na.rm=TRUE)
[1] 1077.1746 681.1065 671.1373 713.5260 791.0175 677.6151 688.3481
[8] 684.7435 714.5815 639.8281 751.6354 736.6040 580.7738 713.2020
[15] 705.7007 703.8890 742.2106 708.2501 687.9559 731.6911
> colVars(tmp5,na.rm=TRUE)
[1] 16144.85476 104.59355 61.56258 110.19870 96.82526 71.66599
[7] 100.35613 38.61612 90.53300 64.17449 62.58516 50.46765
[13] 121.32385 75.26408 121.22189 34.98207 107.36963 98.74334
[19] 56.81817 65.85846
> colSd(tmp5,na.rm=TRUE)
[1] 127.062405 10.227099 7.846183 10.497557 9.839983 8.465577
[7] 10.017791 6.214187 9.514883 8.010898 7.911078 7.104058
[13] 11.014711 8.675487 11.010081 5.914564 10.361932 9.936968
[19] 7.537783 8.115323
> colMax(tmp5,na.rm=TRUE)
[1] 469.12638 85.34453 78.23123 85.96297 91.94425 82.12094 83.91608
[8] 76.08333 85.55394 79.91668 87.37565 81.50387 83.70119 86.82726
[15] 85.57203 81.89936 87.28076 93.64524 81.41760 80.78970
> colMin(tmp5,na.rm=TRUE)
[1] 60.87357 53.78289 53.53748 56.38080 58.44905 58.07376 53.32256 58.15722
[9] 57.71910 53.98576 64.03788 56.88987 52.23236 59.29628 53.45730 64.66739
[17] 61.50715 57.95994 58.57619 59.88072
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.18359 70.13793 67.52863 70.38377 69.88005 74.29987 67.20029 70.18944
[9] 70.55374 NaN
> rowSums(tmp5,na.rm=TRUE)
[1] 1803.672 1402.759 1350.573 1407.675 1397.601 1485.997 1344.006 1403.789
[9] 1411.075 0.000
> rowVars(tmp5,na.rm=TRUE)
[1] 8061.78996 105.50746 47.27068 81.74993 86.21162 69.35622
[7] 83.25774 77.65596 89.57595 NA
> rowSd(tmp5,na.rm=TRUE)
[1] 89.787471 10.271683 6.875368 9.041567 9.285021 8.328038 9.124568
[8] 8.812262 9.464457 NA
> rowMax(tmp5,na.rm=TRUE)
[1] 469.12638 85.57203 84.98060 85.55394 86.82726 93.64524 85.92703
[8] 85.00463 83.70119 NA
> rowMin(tmp5,na.rm=TRUE)
[1] 53.32256 53.98576 53.53748 52.23236 56.88987 59.29628 53.78289 53.45730
[9] 56.38080 NA
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 112.01928 68.71036 66.16755 70.59087 78.46480 66.56106 69.25974
[8] 67.81043 72.11432 64.27594 73.80664 73.77171 NaN 71.73790
[15] 71.32500 70.94476 72.76998 70.40575 67.39315 72.57883
> colSums(tmp5,na.rm=TRUE)
[1] 1008.1735 618.3933 595.5079 635.3178 706.1832 599.0495 623.3376
[8] 610.2939 649.0289 578.4835 664.2597 663.9454 0.0000 645.6411
[15] 641.9250 638.5028 654.9298 633.6517 606.5383 653.2095
> colVars(tmp5,na.rm=TRUE)
[1] 17954.77300 113.62160 59.18622 117.44590 104.36427 64.41206
[7] 110.86931 38.48436 97.00579 71.22963 49.69500 56.63672
[13] NA 82.70929 129.96308 35.87884 97.10254 109.10868
[19] 41.79334 70.17098
> colSd(tmp5,na.rm=TRUE)
[1] 133.995422 10.659343 7.693258 10.837246 10.215883 8.025712
[7] 10.529450 6.203577 9.849152 8.439765 7.049468 7.525737
[13] NA 9.094465 11.400135 5.989895 9.854062 10.445510
[19] 6.464777 8.376812
> colMax(tmp5,na.rm=TRUE)
[1] 469.12638 85.34453 78.23123 85.96297 91.94425 82.12094 83.91608
[8] 76.08333 85.55394 79.91668 84.98060 81.50387 -Inf 86.82726
[15] 85.57203 81.89936 85.00463 93.64524 77.27788 80.78970
> colMin(tmp5,na.rm=TRUE)
[1] 60.87357 53.78289 53.53748 56.38080 58.44905 58.07376 53.32256 58.15722
[9] 57.71910 53.98576 64.03788 56.88987 Inf 59.29628 53.45730 64.66739
[17] 61.50715 57.95994 58.57619 59.88072
>
>
>
>
> 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] 154.9098 244.8521 163.5145 288.3447 228.4803 218.4264 290.7839 182.7754
[9] 198.7815 237.6254
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 154.9098 244.8521 163.5145 288.3447 228.4803 218.4264 290.7839 182.7754
[9] 198.7815 237.6254
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col <- 3
> cat(which.row," ",which.col,"\n")
1 3
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
[1] -8.526513e-14 5.684342e-14 0.000000e+00 0.000000e+00 5.684342e-14
[6] 5.684342e-14 1.421085e-14 -1.705303e-13 2.842171e-14 8.526513e-14
[11] -5.684342e-14 4.263256e-14 1.705303e-13 -2.557954e-13 2.842171e-14
[16] 8.526513e-14 0.000000e+00 0.000000e+00 7.105427e-14 -1.705303e-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 1
4 12
6 1
6 16
4 20
3 4
1 17
9 10
5 17
6 8
5 6
7 12
9 2
10 4
8 4
3 20
4 3
6 19
8 17
1 1
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] 2.1429
> Min(tmp)
[1] -2.10957
> mean(tmp)
[1] 0.1327203
> Sum(tmp)
[1] 13.27203
> Var(tmp)
[1] 0.8836259
>
> rowMeans(tmp)
[1] 0.1327203
> rowSums(tmp)
[1] 13.27203
> rowVars(tmp)
[1] 0.8836259
> rowSd(tmp)
[1] 0.9400138
> rowMax(tmp)
[1] 2.1429
> rowMin(tmp)
[1] -2.10957
>
> colMeans(tmp)
[1] -0.512997497 1.225074969 0.523818521 -0.788529665 -0.390230953
[6] -1.416744547 0.245559227 1.042853734 -0.164047720 -0.684122143
[11] 0.529562131 -0.984406874 0.505161105 -0.134550107 0.075780379
[16] -0.327981029 0.790137033 -0.694381506 0.531510249 -0.035704552
[21] -0.327609555 0.696981598 0.069991120 -0.603034102 -1.112575991
[26] -1.368286225 2.118621799 2.104515801 1.301799779 -0.189248601
[31] 1.207449358 1.568142628 1.465646665 -0.850727485 0.130518430
[36] -1.687558832 -0.748446935 -0.075399626 1.932483071 0.259933963
[41] 0.812916329 -0.122850409 -0.429779982 1.815876799 -1.745122634
[46] -0.694119004 1.982342494 -0.020403205 2.142899927 -1.438371299
[51] -0.017431395 0.073154361 -1.506066901 -0.400805878 0.619763903
[56] 0.582015412 0.499357046 -0.454466207 0.176425665 -0.727534004
[61] 1.961185676 0.002529523 1.253521016 0.653023633 -0.093163961
[66] 1.588747166 0.174735841 -1.421474728 -0.043728856 -0.316647462
[71] 0.794193213 0.760002786 1.254821165 -0.740403322 -0.680836608
[76] 0.223771011 -0.337969372 -2.109570224 -0.288951445 0.222293419
[81] 0.148756260 0.482297458 1.324140849 0.583953781 -0.110934420
[86] 0.630677847 0.774866904 -0.554459074 0.093181949 0.440492867
[91] 0.199608959 0.740667420 -0.382008928 -0.733294123 0.729999147
[96] -1.218407618 0.729654893 -0.980916128 0.267670635 0.873239834
> colSums(tmp)
[1] -0.512997497 1.225074969 0.523818521 -0.788529665 -0.390230953
[6] -1.416744547 0.245559227 1.042853734 -0.164047720 -0.684122143
[11] 0.529562131 -0.984406874 0.505161105 -0.134550107 0.075780379
[16] -0.327981029 0.790137033 -0.694381506 0.531510249 -0.035704552
[21] -0.327609555 0.696981598 0.069991120 -0.603034102 -1.112575991
[26] -1.368286225 2.118621799 2.104515801 1.301799779 -0.189248601
[31] 1.207449358 1.568142628 1.465646665 -0.850727485 0.130518430
[36] -1.687558832 -0.748446935 -0.075399626 1.932483071 0.259933963
[41] 0.812916329 -0.122850409 -0.429779982 1.815876799 -1.745122634
[46] -0.694119004 1.982342494 -0.020403205 2.142899927 -1.438371299
[51] -0.017431395 0.073154361 -1.506066901 -0.400805878 0.619763903
[56] 0.582015412 0.499357046 -0.454466207 0.176425665 -0.727534004
[61] 1.961185676 0.002529523 1.253521016 0.653023633 -0.093163961
[66] 1.588747166 0.174735841 -1.421474728 -0.043728856 -0.316647462
[71] 0.794193213 0.760002786 1.254821165 -0.740403322 -0.680836608
[76] 0.223771011 -0.337969372 -2.109570224 -0.288951445 0.222293419
[81] 0.148756260 0.482297458 1.324140849 0.583953781 -0.110934420
[86] 0.630677847 0.774866904 -0.554459074 0.093181949 0.440492867
[91] 0.199608959 0.740667420 -0.382008928 -0.733294123 0.729999147
[96] -1.218407618 0.729654893 -0.980916128 0.267670635 0.873239834
> 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] -0.512997497 1.225074969 0.523818521 -0.788529665 -0.390230953
[6] -1.416744547 0.245559227 1.042853734 -0.164047720 -0.684122143
[11] 0.529562131 -0.984406874 0.505161105 -0.134550107 0.075780379
[16] -0.327981029 0.790137033 -0.694381506 0.531510249 -0.035704552
[21] -0.327609555 0.696981598 0.069991120 -0.603034102 -1.112575991
[26] -1.368286225 2.118621799 2.104515801 1.301799779 -0.189248601
[31] 1.207449358 1.568142628 1.465646665 -0.850727485 0.130518430
[36] -1.687558832 -0.748446935 -0.075399626 1.932483071 0.259933963
[41] 0.812916329 -0.122850409 -0.429779982 1.815876799 -1.745122634
[46] -0.694119004 1.982342494 -0.020403205 2.142899927 -1.438371299
[51] -0.017431395 0.073154361 -1.506066901 -0.400805878 0.619763903
[56] 0.582015412 0.499357046 -0.454466207 0.176425665 -0.727534004
[61] 1.961185676 0.002529523 1.253521016 0.653023633 -0.093163961
[66] 1.588747166 0.174735841 -1.421474728 -0.043728856 -0.316647462
[71] 0.794193213 0.760002786 1.254821165 -0.740403322 -0.680836608
[76] 0.223771011 -0.337969372 -2.109570224 -0.288951445 0.222293419
[81] 0.148756260 0.482297458 1.324140849 0.583953781 -0.110934420
[86] 0.630677847 0.774866904 -0.554459074 0.093181949 0.440492867
[91] 0.199608959 0.740667420 -0.382008928 -0.733294123 0.729999147
[96] -1.218407618 0.729654893 -0.980916128 0.267670635 0.873239834
> colMin(tmp)
[1] -0.512997497 1.225074969 0.523818521 -0.788529665 -0.390230953
[6] -1.416744547 0.245559227 1.042853734 -0.164047720 -0.684122143
[11] 0.529562131 -0.984406874 0.505161105 -0.134550107 0.075780379
[16] -0.327981029 0.790137033 -0.694381506 0.531510249 -0.035704552
[21] -0.327609555 0.696981598 0.069991120 -0.603034102 -1.112575991
[26] -1.368286225 2.118621799 2.104515801 1.301799779 -0.189248601
[31] 1.207449358 1.568142628 1.465646665 -0.850727485 0.130518430
[36] -1.687558832 -0.748446935 -0.075399626 1.932483071 0.259933963
[41] 0.812916329 -0.122850409 -0.429779982 1.815876799 -1.745122634
[46] -0.694119004 1.982342494 -0.020403205 2.142899927 -1.438371299
[51] -0.017431395 0.073154361 -1.506066901 -0.400805878 0.619763903
[56] 0.582015412 0.499357046 -0.454466207 0.176425665 -0.727534004
[61] 1.961185676 0.002529523 1.253521016 0.653023633 -0.093163961
[66] 1.588747166 0.174735841 -1.421474728 -0.043728856 -0.316647462
[71] 0.794193213 0.760002786 1.254821165 -0.740403322 -0.680836608
[76] 0.223771011 -0.337969372 -2.109570224 -0.288951445 0.222293419
[81] 0.148756260 0.482297458 1.324140849 0.583953781 -0.110934420
[86] 0.630677847 0.774866904 -0.554459074 0.093181949 0.440492867
[91] 0.199608959 0.740667420 -0.382008928 -0.733294123 0.729999147
[96] -1.218407618 0.729654893 -0.980916128 0.267670635 0.873239834
> colMedians(tmp)
[1] -0.512997497 1.225074969 0.523818521 -0.788529665 -0.390230953
[6] -1.416744547 0.245559227 1.042853734 -0.164047720 -0.684122143
[11] 0.529562131 -0.984406874 0.505161105 -0.134550107 0.075780379
[16] -0.327981029 0.790137033 -0.694381506 0.531510249 -0.035704552
[21] -0.327609555 0.696981598 0.069991120 -0.603034102 -1.112575991
[26] -1.368286225 2.118621799 2.104515801 1.301799779 -0.189248601
[31] 1.207449358 1.568142628 1.465646665 -0.850727485 0.130518430
[36] -1.687558832 -0.748446935 -0.075399626 1.932483071 0.259933963
[41] 0.812916329 -0.122850409 -0.429779982 1.815876799 -1.745122634
[46] -0.694119004 1.982342494 -0.020403205 2.142899927 -1.438371299
[51] -0.017431395 0.073154361 -1.506066901 -0.400805878 0.619763903
[56] 0.582015412 0.499357046 -0.454466207 0.176425665 -0.727534004
[61] 1.961185676 0.002529523 1.253521016 0.653023633 -0.093163961
[66] 1.588747166 0.174735841 -1.421474728 -0.043728856 -0.316647462
[71] 0.794193213 0.760002786 1.254821165 -0.740403322 -0.680836608
[76] 0.223771011 -0.337969372 -2.109570224 -0.288951445 0.222293419
[81] 0.148756260 0.482297458 1.324140849 0.583953781 -0.110934420
[86] 0.630677847 0.774866904 -0.554459074 0.093181949 0.440492867
[91] 0.199608959 0.740667420 -0.382008928 -0.733294123 0.729999147
[96] -1.218407618 0.729654893 -0.980916128 0.267670635 0.873239834
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.5129975 1.225075 0.5238185 -0.7885297 -0.390231 -1.416745 0.2455592
[2,] -0.5129975 1.225075 0.5238185 -0.7885297 -0.390231 -1.416745 0.2455592
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 1.042854 -0.1640477 -0.6841221 0.5295621 -0.9844069 0.5051611 -0.1345501
[2,] 1.042854 -0.1640477 -0.6841221 0.5295621 -0.9844069 0.5051611 -0.1345501
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 0.07578038 -0.327981 0.790137 -0.6943815 0.5315102 -0.03570455 -0.3276096
[2,] 0.07578038 -0.327981 0.790137 -0.6943815 0.5315102 -0.03570455 -0.3276096
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 0.6969816 0.06999112 -0.6030341 -1.112576 -1.368286 2.118622 2.104516
[2,] 0.6969816 0.06999112 -0.6030341 -1.112576 -1.368286 2.118622 2.104516
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 1.3018 -0.1892486 1.207449 1.568143 1.465647 -0.8507275 0.1305184
[2,] 1.3018 -0.1892486 1.207449 1.568143 1.465647 -0.8507275 0.1305184
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] -1.687559 -0.7484469 -0.07539963 1.932483 0.259934 0.8129163 -0.1228504
[2,] -1.687559 -0.7484469 -0.07539963 1.932483 0.259934 0.8129163 -0.1228504
[,43] [,44] [,45] [,46] [,47] [,48] [,49] [,50]
[1,] -0.42978 1.815877 -1.745123 -0.694119 1.982342 -0.0204032 2.1429 -1.438371
[2,] -0.42978 1.815877 -1.745123 -0.694119 1.982342 -0.0204032 2.1429 -1.438371
[,51] [,52] [,53] [,54] [,55] [,56] [,57]
[1,] -0.01743139 0.07315436 -1.506067 -0.4008059 0.6197639 0.5820154 0.499357
[2,] -0.01743139 0.07315436 -1.506067 -0.4008059 0.6197639 0.5820154 0.499357
[,58] [,59] [,60] [,61] [,62] [,63] [,64]
[1,] -0.4544662 0.1764257 -0.727534 1.961186 0.002529523 1.253521 0.6530236
[2,] -0.4544662 0.1764257 -0.727534 1.961186 0.002529523 1.253521 0.6530236
[,65] [,66] [,67] [,68] [,69] [,70] [,71]
[1,] -0.09316396 1.588747 0.1747358 -1.421475 -0.04372886 -0.3166475 0.7941932
[2,] -0.09316396 1.588747 0.1747358 -1.421475 -0.04372886 -0.3166475 0.7941932
[,72] [,73] [,74] [,75] [,76] [,77] [,78]
[1,] 0.7600028 1.254821 -0.7404033 -0.6808366 0.223771 -0.3379694 -2.10957
[2,] 0.7600028 1.254821 -0.7404033 -0.6808366 0.223771 -0.3379694 -2.10957
[,79] [,80] [,81] [,82] [,83] [,84] [,85]
[1,] -0.2889514 0.2222934 0.1487563 0.4822975 1.324141 0.5839538 -0.1109344
[2,] -0.2889514 0.2222934 0.1487563 0.4822975 1.324141 0.5839538 -0.1109344
[,86] [,87] [,88] [,89] [,90] [,91] [,92]
[1,] 0.6306778 0.7748669 -0.5544591 0.09318195 0.4404929 0.199609 0.7406674
[2,] 0.6306778 0.7748669 -0.5544591 0.09318195 0.4404929 0.199609 0.7406674
[,93] [,94] [,95] [,96] [,97] [,98] [,99]
[1,] -0.3820089 -0.7332941 0.7299991 -1.218408 0.7296549 -0.9809161 0.2676706
[2,] -0.3820089 -0.7332941 0.7299991 -1.218408 0.7296549 -0.9809161 0.2676706
[,100]
[1,] 0.8732398
[2,] 0.8732398
>
>
> Max(tmp2)
[1] 2.810904
> Min(tmp2)
[1] -2.357971
> mean(tmp2)
[1] -0.04979936
> Sum(tmp2)
[1] -4.979936
> Var(tmp2)
[1] 1.134046
>
> rowMeans(tmp2)
[1] -0.53996310 -0.04086513 1.98181386 -0.83031433 0.50232942 1.75790743
[7] -2.35797065 -0.54276243 -0.27504061 -1.10990345 -0.65822151 -0.56258136
[13] 0.84457689 -0.16637227 -0.36908701 -0.91618229 -0.39073502 0.15261037
[19] -0.94869948 0.66946249 -0.13569771 0.59447345 -0.56598480 -0.33021778
[25] 0.33262636 -0.21059907 1.25177043 1.51538348 0.61460732 -0.66201526
[31] -1.33774433 -0.67323958 -0.99228952 -1.52704164 0.13204100 -0.20236726
[37] 0.86691346 -0.90050023 -0.72082700 -0.05737677 0.03512894 1.65953199
[43] -1.92941654 2.81090365 -1.99124670 -0.40468847 -0.63619714 2.03884191
[49] -0.52756976 0.01245859 1.14029459 -1.00396814 -1.18351368 0.05332454
[55] -0.42191925 -1.15445407 -1.08790474 -0.82604112 -1.58823793 1.37280677
[61] 0.54402939 0.95997586 -0.63748807 0.57878981 1.32455753 -1.53585876
[67] -0.13144068 1.70973657 0.45989494 0.39688353 0.82215848 1.41564771
[73] -0.12309756 0.36447998 1.69058939 0.80587492 0.95698706 0.46561511
[79] 2.01692257 0.96865576 -1.72829322 0.15653263 1.51673986 -0.90046863
[85] -0.67772826 -0.14684012 -1.87289213 0.44882372 0.27192216 -0.43910917
[91] -0.81659613 1.28146751 -0.28345399 -0.56356684 -0.24628496 -2.19283642
[97] -0.65189850 1.44492333 -1.11731794 -1.07602228
> rowSums(tmp2)
[1] -0.53996310 -0.04086513 1.98181386 -0.83031433 0.50232942 1.75790743
[7] -2.35797065 -0.54276243 -0.27504061 -1.10990345 -0.65822151 -0.56258136
[13] 0.84457689 -0.16637227 -0.36908701 -0.91618229 -0.39073502 0.15261037
[19] -0.94869948 0.66946249 -0.13569771 0.59447345 -0.56598480 -0.33021778
[25] 0.33262636 -0.21059907 1.25177043 1.51538348 0.61460732 -0.66201526
[31] -1.33774433 -0.67323958 -0.99228952 -1.52704164 0.13204100 -0.20236726
[37] 0.86691346 -0.90050023 -0.72082700 -0.05737677 0.03512894 1.65953199
[43] -1.92941654 2.81090365 -1.99124670 -0.40468847 -0.63619714 2.03884191
[49] -0.52756976 0.01245859 1.14029459 -1.00396814 -1.18351368 0.05332454
[55] -0.42191925 -1.15445407 -1.08790474 -0.82604112 -1.58823793 1.37280677
[61] 0.54402939 0.95997586 -0.63748807 0.57878981 1.32455753 -1.53585876
[67] -0.13144068 1.70973657 0.45989494 0.39688353 0.82215848 1.41564771
[73] -0.12309756 0.36447998 1.69058939 0.80587492 0.95698706 0.46561511
[79] 2.01692257 0.96865576 -1.72829322 0.15653263 1.51673986 -0.90046863
[85] -0.67772826 -0.14684012 -1.87289213 0.44882372 0.27192216 -0.43910917
[91] -0.81659613 1.28146751 -0.28345399 -0.56356684 -0.24628496 -2.19283642
[97] -0.65189850 1.44492333 -1.11731794 -1.07602228
> 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] -0.53996310 -0.04086513 1.98181386 -0.83031433 0.50232942 1.75790743
[7] -2.35797065 -0.54276243 -0.27504061 -1.10990345 -0.65822151 -0.56258136
[13] 0.84457689 -0.16637227 -0.36908701 -0.91618229 -0.39073502 0.15261037
[19] -0.94869948 0.66946249 -0.13569771 0.59447345 -0.56598480 -0.33021778
[25] 0.33262636 -0.21059907 1.25177043 1.51538348 0.61460732 -0.66201526
[31] -1.33774433 -0.67323958 -0.99228952 -1.52704164 0.13204100 -0.20236726
[37] 0.86691346 -0.90050023 -0.72082700 -0.05737677 0.03512894 1.65953199
[43] -1.92941654 2.81090365 -1.99124670 -0.40468847 -0.63619714 2.03884191
[49] -0.52756976 0.01245859 1.14029459 -1.00396814 -1.18351368 0.05332454
[55] -0.42191925 -1.15445407 -1.08790474 -0.82604112 -1.58823793 1.37280677
[61] 0.54402939 0.95997586 -0.63748807 0.57878981 1.32455753 -1.53585876
[67] -0.13144068 1.70973657 0.45989494 0.39688353 0.82215848 1.41564771
[73] -0.12309756 0.36447998 1.69058939 0.80587492 0.95698706 0.46561511
[79] 2.01692257 0.96865576 -1.72829322 0.15653263 1.51673986 -0.90046863
[85] -0.67772826 -0.14684012 -1.87289213 0.44882372 0.27192216 -0.43910917
[91] -0.81659613 1.28146751 -0.28345399 -0.56356684 -0.24628496 -2.19283642
[97] -0.65189850 1.44492333 -1.11731794 -1.07602228
> rowMin(tmp2)
[1] -0.53996310 -0.04086513 1.98181386 -0.83031433 0.50232942 1.75790743
[7] -2.35797065 -0.54276243 -0.27504061 -1.10990345 -0.65822151 -0.56258136
[13] 0.84457689 -0.16637227 -0.36908701 -0.91618229 -0.39073502 0.15261037
[19] -0.94869948 0.66946249 -0.13569771 0.59447345 -0.56598480 -0.33021778
[25] 0.33262636 -0.21059907 1.25177043 1.51538348 0.61460732 -0.66201526
[31] -1.33774433 -0.67323958 -0.99228952 -1.52704164 0.13204100 -0.20236726
[37] 0.86691346 -0.90050023 -0.72082700 -0.05737677 0.03512894 1.65953199
[43] -1.92941654 2.81090365 -1.99124670 -0.40468847 -0.63619714 2.03884191
[49] -0.52756976 0.01245859 1.14029459 -1.00396814 -1.18351368 0.05332454
[55] -0.42191925 -1.15445407 -1.08790474 -0.82604112 -1.58823793 1.37280677
[61] 0.54402939 0.95997586 -0.63748807 0.57878981 1.32455753 -1.53585876
[67] -0.13144068 1.70973657 0.45989494 0.39688353 0.82215848 1.41564771
[73] -0.12309756 0.36447998 1.69058939 0.80587492 0.95698706 0.46561511
[79] 2.01692257 0.96865576 -1.72829322 0.15653263 1.51673986 -0.90046863
[85] -0.67772826 -0.14684012 -1.87289213 0.44882372 0.27192216 -0.43910917
[91] -0.81659613 1.28146751 -0.28345399 -0.56356684 -0.24628496 -2.19283642
[97] -0.65189850 1.44492333 -1.11731794 -1.07602228
>
> colMeans(tmp2)
[1] -0.04979936
> colSums(tmp2)
[1] -4.979936
> colVars(tmp2)
[1] 1.134046
> colSd(tmp2)
[1] 1.064916
> colMax(tmp2)
[1] 2.810904
> colMin(tmp2)
[1] -2.357971
> colMedians(tmp2)
[1] -0.1843698
> colRanges(tmp2)
[,1]
[1,] -2.357971
[2,] 2.810904
>
> 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] 5.3313405 2.4270893 1.1858259 -0.7947470 -1.3715938 1.2083871
[7] 3.8885258 4.4269503 0.2021074 -8.4104211
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.42525554
[2,] 0.05193506
[3,] 0.39844874
[4,] 0.98189865
[5,] 2.50330044
>
> rowApply(tmp,sum)
[1] 1.349821 6.057398 3.219197 -1.981882 -2.641739 -1.250818 6.429268
[8] -6.768204 1.398520 2.281903
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 5 9 7 2 10 6 3 10 6 6
[2,] 3 2 2 10 5 10 7 7 10 1
[3,] 9 5 4 5 7 8 6 8 3 4
[4,] 10 6 1 7 2 3 4 6 2 10
[5,] 4 10 8 6 6 2 1 1 8 5
[6,] 8 3 5 9 1 4 5 9 7 7
[7,] 2 8 6 3 8 7 10 5 4 9
[8,] 6 7 9 4 3 9 8 4 9 8
[9,] 1 4 10 8 9 5 9 2 1 3
[10,] 7 1 3 1 4 1 2 3 5 2
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -0.8090351 2.0315793 -4.0492697 1.7288656 4.9153116 2.7473509
[7] 3.6868986 -2.3708582 -2.2105845 -0.3440734 -0.8810260 -2.5393503
[13] 3.1865214 -0.2430247 -0.3376909 0.2443471 -0.4067989 0.4004154
[19] -0.6032059 -5.2779831
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.054274282
[2,] -0.118370962
[3,] -0.047337938
[4,] -0.007583411
[5,] 0.418531514
>
> rowApply(tmp,sum)
[1] -2.576599 -3.674635 2.098655 1.080334 1.940634
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 11 13 14 3 10
[2,] 4 20 12 19 1
[3,] 10 4 3 2 3
[4,] 9 18 18 7 16
[5,] 20 19 16 14 14
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -0.047337938 -1.1235143 -0.1805786 -0.3332427 1.3685703 0.6241047
[2,] -0.118370962 2.2230093 -1.2054392 1.0323575 1.8947065 -1.2996302
[3,] 0.418531514 0.2963958 -1.0231741 1.0283774 0.8620204 0.2320045
[4,] -1.054274282 1.9927635 -1.1687131 -0.6696549 0.3592924 2.5561463
[5,] -0.007583411 -1.3570751 -0.4713646 0.6710283 0.4307220 0.6347256
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 1.26189615 -1.80659995 -0.6249301 -0.5391242 0.2696236 -0.6302065
[2,] 0.18237550 0.10661602 -0.6951946 -0.2541067 -0.3392345 -1.1130136
[3,] 1.93063989 -0.38886055 -0.2337780 -0.2410912 1.0201928 -1.8843492
[4,] -0.01719864 0.02134447 -0.4894376 0.9000280 -1.0048423 0.6754573
[5,] 0.32918573 -0.30335821 -0.1672443 -0.2097793 -0.8267656 0.4127617
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 1.08837473 -0.4993000 0.1764785 0.83566947 0.3012185 0.5997091
[2,] -0.04129806 0.9879199 -0.6431259 -0.24498623 -0.1280091 -0.6613956
[3,] 1.31458189 0.7953992 -0.2887991 -0.59795013 -0.5888838 0.4144269
[4,] -0.32547464 -1.3203937 0.7270829 0.01750549 -0.8125189 -0.8012492
[5,] 1.15033751 -0.2066501 -0.3093272 0.23410848 0.8213944 0.8489242
[,19] [,20]
[1,] -1.57533769 -1.7420717
[2,] -1.64839117 -1.7094239
[3,] 0.09626851 -1.0632973
[4,] 1.79530697 -0.3008364
[5,] 0.72894749 -0.4623538
>
>
> 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 : 653 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 : 565 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 -0.01390485 0.0175874 0.3480905 0.6724981 -0.5394738 0.4424548 -0.4396582
col8 col9 col10 col11 col12 col13 col14
row1 0.3384804 -1.223344 0.372139 -1.304761 0.8271776 1.308937 0.02882933
col15 col16 col17 col18 col19 col20
row1 -0.6033706 -0.5758766 0.3050577 0.001134955 0.09042955 0.453136
> tmp[,"col10"]
col10
row1 0.3721390
row2 -0.2011635
row3 -0.7076388
row4 -0.2949861
row5 -0.1324405
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 -0.01390485 0.0175874 0.3480905 0.6724981 -0.5394738 0.4424548 -0.4396582
row5 1.14307362 0.2192473 1.3691853 -0.2643929 1.9060046 1.2501656 -0.6839206
col8 col9 col10 col11 col12 col13 col14
row1 0.3384804 -1.223344 0.3721390 -1.304761 0.8271776 1.30893652 0.02882933
row5 1.8401962 1.670055 -0.1324405 -1.007141 0.5188389 0.08745175 0.67645742
col15 col16 col17 col18 col19 col20
row1 -0.6033706 -0.575876602 0.3050577 0.001134955 0.09042955 0.45313600
row5 0.2222708 0.009394869 -0.8388810 0.427254169 0.99404289 0.03919614
> tmp[,c("col6","col20")]
col6 col20
row1 0.4424548 0.45313600
row2 -0.4852310 2.22744479
row3 -1.7339681 -0.42095379
row4 0.4046668 1.93625278
row5 1.2501656 0.03919614
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 0.4424548 0.45313600
row5 1.2501656 0.03919614
>
>
>
>
> 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 48.96623 49.89211 51.24561 51.91913 49.70566 105.5414 50.96708 49.15158
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.43712 48.13259 49.24516 49.88238 50.87713 50.16426 49.66919 50.61252
col17 col18 col19 col20
row1 49.0365 50.54541 51.04494 105.8727
> tmp[,"col10"]
col10
row1 48.13259
row2 30.49025
row3 30.33344
row4 29.91380
row5 50.27971
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 48.96623 49.89211 51.24561 51.91913 49.70566 105.5414 50.96708 49.15158
row5 50.96196 50.76369 51.01781 49.90877 49.15368 104.9087 50.34245 51.25492
col9 col10 col11 col12 col13 col14 col15 col16
row1 50.43712 48.13259 49.24516 49.88238 50.87713 50.16426 49.66919 50.61252
row5 47.94738 50.27971 49.07771 50.49188 50.97714 50.98106 50.47893 50.59588
col17 col18 col19 col20
row1 49.03650 50.54541 51.04494 105.8727
row5 50.20457 49.73377 50.44051 103.6526
> tmp[,c("col6","col20")]
col6 col20
row1 105.54142 105.87267
row2 75.69894 76.47087
row3 74.02743 74.75419
row4 75.59712 76.64695
row5 104.90868 103.65260
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.5414 105.8727
row5 104.9087 103.6526
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.5414 105.8727
row5 104.9087 103.6526
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -1.1007020
[2,] 1.0489149
[3,] 0.1293805
[4,] -2.8457536
[5,] -0.4284468
> tmp[,c("col17","col7")]
col17 col7
[1,] -1.4119862 -0.8426982
[2,] -3.0863359 0.9319411
[3,] -1.0978400 -0.6525221
[4,] 0.7589559 1.7140268
[5,] -0.7826799 2.5125020
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -0.4709030 0.01256435
[2,] 0.3448938 -1.03257919
[3,] 0.6411385 -1.60628769
[4,] 0.4112791 2.78071406
[5,] 0.5799154 -1.41371071
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -0.470903
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -0.4709030
[2,] 0.3448938
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6]
row3 -0.6790226 -0.9474662 0.99835911 0.979789 -1.164688 -0.2285523
row1 -0.3725011 0.6224032 -0.06845613 -1.302232 -1.535774 1.6756279
[,7] [,8] [,9] [,10] [,11] [,12]
row3 -0.03692157 0.8555469 -1.3786349 -1.7007777 -2.0404754 -1.057555
row1 1.63398100 -2.0321380 0.3759219 0.1701209 0.5498237 1.934667
[,13] [,14] [,15] [,16] [,17] [,18] [,19]
row3 -1.1322614 -0.5260751 0.9829954 -1.1879790 -1.1221508 2.8023136 1.787263
row1 0.8512705 -0.4636727 -1.4347783 0.2686323 -0.0559467 0.2756371 1.380948
[,20]
row3 -1.915831
row1 -1.183302
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6]
row2 -0.3034366 -0.09892219 0.5827958 -0.7858715 -0.6145146 -0.06412621
[,7] [,8] [,9] [,10]
row2 -0.7262639 0.9919746 -1.633407 -0.5362008
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -0.3798113 0.8060911 1.336181 -0.2580035 -1.828174 -2.667466 -0.9487971
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.2377793 1.073414 -1.13255 -0.5190159 -0.5223979 1.290234 -2.194031
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.6220075 0.5770493 -0.6567707 0.1467224 -0.5619079 -0.5203392
>
>
> 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: 0x14cdddb0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1963975523127b"
[2] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM19639741e95a9c"
[3] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM19639710b267fe"
[4] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM196397336140c1"
[5] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM19639730109ca6"
[6] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM196397691f9d12"
[7] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1963976d875a2"
[8] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM196397203e4b06"
[9] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM19639728ea8596"
[10] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM19639778c44971"
[11] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM196397657375ec"
[12] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM196397237924a1"
[13] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1963976b7ffe39"
[14] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM1963973c281743"
[15] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM19639727f7c08a"
>
>
> ### 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: 0x151b5b90>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x151b5b90>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x151b5b90>
> rowMedians(tmp)
[1] -0.2894033938 0.5063442014 -0.0403022421 0.1220251088 0.1816357025
[6] -0.0695060518 0.3833660224 -0.1264167617 0.3426498809 0.0577914470
[11] -0.1894787435 0.4605784004 0.0495623035 -0.1444851730 0.1121980145
[16] -0.2335230418 -0.6599042772 0.0626342017 -0.3284735086 -0.4998301318
[21] -0.4766932420 0.2059340983 -0.0117747948 -0.2588760095 -0.2213489883
[26] -0.1522729323 -0.2762500328 -0.3759551237 0.6600212789 -0.4507504711
[31] 0.2089464211 -0.0188885962 0.0399568632 -0.2111786027 -0.1622324464
[36] 0.3240700051 0.6237222279 -0.3399521827 0.1510881637 0.2793497770
[41] -0.0187891508 -0.3028976363 -0.5159974180 -0.0381060625 0.5159685698
[46] 0.2446378017 0.5232108546 0.0847214156 0.2830578945 -0.2546610781
[51] -0.0604968737 -0.2600354127 -0.0753011814 0.4672002476 -0.2110367682
[56] -0.0155808200 -0.1465807801 0.5843059549 -0.2407676587 0.3036742630
[61] 0.4163785877 -0.3895760691 -0.8520813775 -0.4353165401 0.4329905821
[66] -0.0238269064 0.1783162115 -0.4061624069 0.1438796272 0.3278906078
[71] -0.2316035683 -0.1473737845 0.1327240469 -0.1058878232 0.1064584844
[76] -0.1436548688 -0.2243022920 -0.2166567215 -0.0835918088 0.4187075086
[81] 0.0038633484 -0.1264509893 0.0463006965 0.0437640652 0.2008336784
[86] -0.3328449901 -0.0849399086 -0.0081559973 -0.3642770645 0.2505147548
[91] 0.1443232491 -0.1308015120 -0.0730758260 0.3425044891 0.0012178499
[96] 0.0973295360 -0.1434065457 -0.0259189351 -0.1146428306 0.2548536913
[101] -0.6476862373 -0.0252804720 0.1813272610 -0.1329415516 -0.5813979816
[106] 0.1100117884 0.2186894541 0.0477075709 -0.4242840449 -0.0004159030
[111] -0.1061319122 0.0217990401 0.1780613560 -0.6005341214 0.2139847637
[116] -0.2297055448 -0.1245198142 -0.2772830056 -0.2857740651 0.1732087980
[121] -0.3065547731 -0.4958174199 0.0545089252 -0.1435228360 0.1716025688
[126] 0.1900431799 0.1860147601 0.0547644261 0.1619526987 -0.0813831620
[131] 0.2191773794 0.1787346523 -0.1614341131 -0.2263093900 -0.6218579645
[136] -0.2770851440 0.4926750546 -0.1666217449 0.0767149265 -0.2335557647
[141] 0.0982739522 0.4133746861 -0.2045138860 0.2181035301 0.3337390660
[146] -0.2057791138 -0.3354906123 -0.3420527321 0.3130688993 -0.1540560578
[151] -0.2218063986 0.4345814316 0.2168943539 0.0771529117 -0.6922671818
[156] -0.0395318322 0.3918097557 -0.0217761134 0.1546970665 0.2625667465
[161] 0.0075351590 0.4593454401 -0.3372601225 0.0171385414 -0.2770116845
[166] -0.5565101449 0.1886203032 0.1097072175 -0.2734941133 -0.0342300790
[171] -0.2098959044 0.2864409394 0.2584934240 -0.6109701917 0.1486709053
[176] -0.3711317690 -0.0003643115 -0.8092801139 0.1136653363 -0.1273146146
[181] -0.1426655677 0.1170501640 0.2189150669 -0.2123431179 0.0219931134
[186] 0.5269873781 0.4798409025 -0.1202904428 0.4256904891 0.5212504062
[191] -0.1975677247 -0.1575001905 0.2568099774 0.2554369456 -0.3870862595
[196] -0.2507278873 -0.1145591118 -0.1002286030 -0.5658341533 0.1342771652
[201] 0.1397891064 0.3199022064 0.2332775970 0.2718272969 -0.2764340209
[206] -0.1108219864 0.1171713330 -0.1383316353 -0.0144922549 -0.2705536957
[211] -1.0961760437 -0.0959350337 -0.4720173274 -0.3710713069 0.4629124434
[216] 0.2268692344 -0.3693654772 0.3326969305 -0.0904765002 -0.4712106273
[221] -0.1213721377 -0.1062010825 -0.3354765312 0.3343869286 -0.3280324813
[226] -0.1996482167 -0.2212581846 0.0157280231 -0.0370451317 -0.3773995924
>
> proc.time()
user system elapsed
1.912 0.867 2.804
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: 0x4b33ff0>
> .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: 0x4b33ff0>
> .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: 0x4b33ff0>
> .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: 0x4b33ff0>
> 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: 0x4a3e470>
> .Call("R_bm_AddColumn",P)
<pointer: 0x4a3e470>
> .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: 0x4a3e470>
> .Call("R_bm_AddColumn",P)
<pointer: 0x4a3e470>
> .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: 0x4a3e470>
> 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: 0x4a190e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x4a190e0>
> .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: 0x4a190e0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x4a190e0>
> .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: 0x4a190e0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x4a190e0>
> .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: 0x4a190e0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x4a190e0>
> .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: 0x4a190e0>
> 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: 0x39a0520>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x39a0520>
> .Call("R_bm_AddColumn",P)
<pointer: 0x39a0520>
> .Call("R_bm_AddColumn",P)
<pointer: 0x39a0520>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1964ea3357309b" "BufferedMatrixFile1964ea6f57446a"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1964ea3357309b" "BufferedMatrixFile1964ea6f57446a"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x58e9030>
> .Call("R_bm_AddColumn",P)
<pointer: 0x58e9030>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x58e9030>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x58e9030>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x58e9030>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x58e9030>
> .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: 0x42b45c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x42b45c0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x42b45c0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x42b45c0>
> 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: 0x5394f30>
> .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: 0x5394f30>
> rm(P)
>
> proc.time()
user system elapsed
0.326 0.065 0.376
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.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.341 0.045 0.371