Ben Bolstad
| Snapshot Date: 2025-10-13 13:45 -0400 (Mon, 13 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 2025-10-14 12:07 -0400 (Tue, 14 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" | 4864 |
| lconway | macOS 12.7.1 Monterey | x86_64 | 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root" | 4652 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root" | 4597 |
| taishan | Linux (openEuler 24.03 LTS) | aarch64 | 4.5.0 (2025-04-11) -- "How About a Twenty-Six" | 4610 |
| 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 255/2346 | 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: 2025-10-14 06:18:14 -0000 (Tue, 14 Oct 2025) |
| EndedAt: 2025-10-14 06:18:37 -0000 (Tue, 14 Oct 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
0.338 0.028 0.351
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 14 06:18:31 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 14 06:18:31 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: 0x2fdd7ff0>
>
>
>
> 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 14 06:18:31 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 14 06:18:31 2025"
>
> ColMode(tmp2)
<pointer: 0x2fdd7ff0>
>
>
>
> ### 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,] 100.3436528 0.8595039 -0.8507083 -0.4779330
[2,] 2.4006578 -0.3422372 0.2392378 -1.4528520
[3,] 0.6851591 -1.9462830 -0.2333785 -0.3399717
[4,] -0.1846319 1.7714634 0.1688249 -1.6389318
> 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 : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 100.3436528 0.8595039 0.8507083 0.4779330
[2,] 2.4006578 0.3422372 0.2392378 1.4528520
[3,] 0.6851591 1.9462830 0.2333785 0.3399717
[4,] 0.1846319 1.7714634 0.1688249 1.6389318
> 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 : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 10.0171679 0.9270944 0.9223385 0.6913270
[2,] 1.5494056 0.5850104 0.4891194 1.2053431
[3,] 0.8277434 1.3950925 0.4830926 0.5830709
[4,] 0.4296881 1.3309633 0.4108831 1.2802077
>
> 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 : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 225.51533 35.13045 35.07409 32.39120
[2,] 42.89471 31.19234 30.13043 38.50628
[3,] 33.96259 40.89721 30.06430 31.17068
[4,] 29.48151 40.08110 29.27766 39.44101
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x310079a0>
> exp(tmp5)
<pointer: 0x310079a0>
> log(tmp5,2)
<pointer: 0x310079a0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 469.3806
> Min(tmp5)
[1] 53.13773
> mean(tmp5)
[1] 73.58066
> Sum(tmp5)
[1] 14716.13
> Var(tmp5)
[1] 875.063
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 90.21472 70.73417 72.65720 70.74809 72.47832 69.60516 74.51673 72.26548
[9] 71.05680 71.52993
> rowSums(tmp5)
[1] 1804.294 1414.683 1453.144 1414.962 1449.566 1392.103 1490.335 1445.310
[9] 1421.136 1430.599
> rowVars(tmp5)
[1] 8041.53848 107.29022 56.69263 85.94736 115.57499 48.11909
[7] 108.63710 82.58178 77.93878 99.89534
> rowSd(tmp5)
[1] 89.674626 10.358099 7.529451 9.270780 10.750581 6.936792 10.422912
[8] 9.087452 8.828294 9.994766
> rowMax(tmp5)
[1] 469.38062 89.27973 86.96927 87.21062 90.17564 86.34396 97.25470
[8] 84.29500 87.28444 88.85910
> rowMin(tmp5)
[1] 56.95666 55.10996 62.57491 53.13773 54.50826 60.34968 57.29754 54.15177
[9] 57.17635 55.06896
>
> colMeans(tmp5)
[1] 113.52050 76.72345 69.49325 73.35543 69.93203 66.62919 71.90441
[8] 68.97192 75.75733 73.29864 64.89479 69.58010 70.12053 72.77239
[15] 73.00365 69.12832 72.00485 72.88380 75.37297 72.26564
> colSums(tmp5)
[1] 1135.2050 767.2345 694.9325 733.5543 699.3203 666.2919 719.0441
[8] 689.7192 757.5733 732.9864 648.9479 695.8010 701.2053 727.7239
[15] 730.0365 691.2832 720.0485 728.8380 753.7297 722.6564
> colVars(tmp5)
[1] 15721.68149 42.51740 65.54665 30.79689 95.89437 86.56012
[7] 53.18606 145.82156 111.82149 187.09546 68.44674 118.69313
[13] 108.44340 45.13956 102.97940 68.30667 118.89558 28.55352
[19] 51.11446 47.70975
> colSd(tmp5)
[1] 125.386130 6.520537 8.096088 5.549494 9.792567 9.303769
[7] 7.292877 12.075660 10.574568 13.678284 8.273254 10.894637
[13] 10.413616 6.718598 10.147876 8.264785 10.903925 5.343550
[19] 7.149438 6.907224
> colMax(tmp5)
[1] 469.38062 85.12218 87.07533 82.09129 86.25713 82.50912 82.02821
[8] 91.44903 87.28444 97.25470 82.78518 88.05433 90.17564 82.14174
[15] 91.41732 87.21062 88.85910 81.44612 84.71512 82.53242
> colMin(tmp5)
[1] 61.36191 64.92277 60.93760 64.87769 53.13773 55.10996 57.58947 56.09678
[9] 56.52570 54.15177 54.50826 56.93747 55.06896 59.18612 57.99861 59.68132
[17] 55.00005 64.71903 60.28788 61.83127
>
>
> ### 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] 90.21472 70.73417 72.65720 70.74809 NA 69.60516 74.51673 72.26548
[9] 71.05680 71.52993
> rowSums(tmp5)
[1] 1804.294 1414.683 1453.144 1414.962 NA 1392.103 1490.335 1445.310
[9] 1421.136 1430.599
> rowVars(tmp5)
[1] 8041.53848 107.29022 56.69263 85.94736 119.32161 48.11909
[7] 108.63710 82.58178 77.93878 99.89534
> rowSd(tmp5)
[1] 89.674626 10.358099 7.529451 9.270780 10.923443 6.936792 10.422912
[8] 9.087452 8.828294 9.994766
> rowMax(tmp5)
[1] 469.38062 89.27973 86.96927 87.21062 NA 86.34396 97.25470
[8] 84.29500 87.28444 88.85910
> rowMin(tmp5)
[1] 56.95666 55.10996 62.57491 53.13773 NA 60.34968 57.29754 54.15177
[9] 57.17635 55.06896
>
> colMeans(tmp5)
[1] 113.52050 76.72345 69.49325 73.35543 69.93203 66.62919 71.90441
[8] 68.97192 75.75733 73.29864 64.89479 69.58010 70.12053 72.77239
[15] NA 69.12832 72.00485 72.88380 75.37297 72.26564
> colSums(tmp5)
[1] 1135.2050 767.2345 694.9325 733.5543 699.3203 666.2919 719.0441
[8] 689.7192 757.5733 732.9864 648.9479 695.8010 701.2053 727.7239
[15] NA 691.2832 720.0485 728.8380 753.7297 722.6564
> colVars(tmp5)
[1] 15721.68149 42.51740 65.54665 30.79689 95.89437 86.56012
[7] 53.18606 145.82156 111.82149 187.09546 68.44674 118.69313
[13] 108.44340 45.13956 NA 68.30667 118.89558 28.55352
[19] 51.11446 47.70975
> colSd(tmp5)
[1] 125.386130 6.520537 8.096088 5.549494 9.792567 9.303769
[7] 7.292877 12.075660 10.574568 13.678284 8.273254 10.894637
[13] 10.413616 6.718598 NA 8.264785 10.903925 5.343550
[19] 7.149438 6.907224
> colMax(tmp5)
[1] 469.38062 85.12218 87.07533 82.09129 86.25713 82.50912 82.02821
[8] 91.44903 87.28444 97.25470 82.78518 88.05433 90.17564 82.14174
[15] NA 87.21062 88.85910 81.44612 84.71512 82.53242
> colMin(tmp5)
[1] 61.36191 64.92277 60.93760 64.87769 53.13773 55.10996 57.58947 56.09678
[9] 56.52570 54.15177 54.50826 56.93747 55.06896 59.18612 NA 59.68132
[17] 55.00005 64.71903 60.28788 61.83127
>
> Max(tmp5,na.rm=TRUE)
[1] 469.3806
> Min(tmp5,na.rm=TRUE)
[1] 53.13773
> mean(tmp5,na.rm=TRUE)
[1] 73.55222
> Sum(tmp5,na.rm=TRUE)
[1] 14636.89
> Var(tmp5,na.rm=TRUE)
[1] 879.3199
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.21472 70.73417 72.65720 70.74809 72.12241 69.60516 74.51673 72.26548
[9] 71.05680 71.52993
> rowSums(tmp5,na.rm=TRUE)
[1] 1804.294 1414.683 1453.144 1414.962 1370.326 1392.103 1490.335 1445.310
[9] 1421.136 1430.599
> rowVars(tmp5,na.rm=TRUE)
[1] 8041.53848 107.29022 56.69263 85.94736 119.32161 48.11909
[7] 108.63710 82.58178 77.93878 99.89534
> rowSd(tmp5,na.rm=TRUE)
[1] 89.674626 10.358099 7.529451 9.270780 10.923443 6.936792 10.422912
[8] 9.087452 8.828294 9.994766
> rowMax(tmp5,na.rm=TRUE)
[1] 469.38062 89.27973 86.96927 87.21062 90.17564 86.34396 97.25470
[8] 84.29500 87.28444 88.85910
> rowMin(tmp5,na.rm=TRUE)
[1] 56.95666 55.10996 62.57491 53.13773 54.50826 60.34968 57.29754 54.15177
[9] 57.17635 55.06896
>
> colMeans(tmp5,na.rm=TRUE)
[1] 113.52050 76.72345 69.49325 73.35543 69.93203 66.62919 71.90441
[8] 68.97192 75.75733 73.29864 64.89479 69.58010 70.12053 72.77239
[15] 72.31065 69.12832 72.00485 72.88380 75.37297 72.26564
> colSums(tmp5,na.rm=TRUE)
[1] 1135.2050 767.2345 694.9325 733.5543 699.3203 666.2919 719.0441
[8] 689.7192 757.5733 732.9864 648.9479 695.8010 701.2053 727.7239
[15] 650.7959 691.2832 720.0485 728.8380 753.7297 722.6564
> colVars(tmp5,na.rm=TRUE)
[1] 15721.68149 42.51740 65.54665 30.79689 95.89437 86.56012
[7] 53.18606 145.82156 111.82149 187.09546 68.44674 118.69313
[13] 108.44340 45.13956 110.44904 68.30667 118.89558 28.55352
[19] 51.11446 47.70975
> colSd(tmp5,na.rm=TRUE)
[1] 125.386130 6.520537 8.096088 5.549494 9.792567 9.303769
[7] 7.292877 12.075660 10.574568 13.678284 8.273254 10.894637
[13] 10.413616 6.718598 10.509474 8.264785 10.903925 5.343550
[19] 7.149438 6.907224
> colMax(tmp5,na.rm=TRUE)
[1] 469.38062 85.12218 87.07533 82.09129 86.25713 82.50912 82.02821
[8] 91.44903 87.28444 97.25470 82.78518 88.05433 90.17564 82.14174
[15] 91.41732 87.21062 88.85910 81.44612 84.71512 82.53242
> colMin(tmp5,na.rm=TRUE)
[1] 61.36191 64.92277 60.93760 64.87769 53.13773 55.10996 57.58947 56.09678
[9] 56.52570 54.15177 54.50826 56.93747 55.06896 59.18612 57.99861 59.68132
[17] 55.00005 64.71903 60.28788 61.83127
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 90.21472 70.73417 72.65720 70.74809 NaN 69.60516 74.51673 72.26548
[9] 71.05680 71.52993
> rowSums(tmp5,na.rm=TRUE)
[1] 1804.294 1414.683 1453.144 1414.962 0.000 1392.103 1490.335 1445.310
[9] 1421.136 1430.599
> rowVars(tmp5,na.rm=TRUE)
[1] 8041.53848 107.29022 56.69263 85.94736 NA 48.11909
[7] 108.63710 82.58178 77.93878 99.89534
> rowSd(tmp5,na.rm=TRUE)
[1] 89.674626 10.358099 7.529451 9.270780 NA 6.936792 10.422912
[8] 9.087452 8.828294 9.994766
> rowMax(tmp5,na.rm=TRUE)
[1] 469.38062 89.27973 86.96927 87.21062 NA 86.34396 97.25470
[8] 84.29500 87.28444 88.85910
> rowMin(tmp5,na.rm=TRUE)
[1] 56.95666 55.10996 62.57491 53.13773 NA 60.34968 57.29754 54.15177
[9] 57.17635 55.06896
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 117.14353 77.04743 69.13549 73.65827 68.92393 64.86475 72.60771
[8] 69.08797 77.89418 72.51900 66.04885 67.52741 67.89218 72.84677
[15] NaN 69.85465 73.89427 73.04582 74.33496 73.42501
> colSums(tmp5,na.rm=TRUE)
[1] 1054.2917 693.4269 622.2194 662.9244 620.3154 583.7828 653.4694
[8] 621.7917 701.0477 652.6710 594.4396 607.7467 611.0296 655.6209
[15] 0.0000 628.6919 665.0484 657.4123 669.0146 660.8251
> colVars(tmp5,na.rm=TRUE)
[1] 17539.22043 46.65119 72.30005 33.61480 96.44836 62.35622
[7] 54.26981 163.89776 74.43029 203.64420 62.01925 86.12736
[13] 66.13666 50.71976 NA 70.90994 93.59596 31.82739
[19] 45.38213 38.55179
> colSd(tmp5,na.rm=TRUE)
[1] 132.435722 6.830168 8.502944 5.797827 9.820813 7.896595
[7] 7.366805 12.802256 8.627299 14.270396 7.875230 9.280483
[13] 8.132445 7.121781 NA 8.420804 9.674500 5.641577
[19] 6.736626 6.209009
> colMax(tmp5,na.rm=TRUE)
[1] 469.38062 85.12218 87.07533 82.09129 86.25713 81.35107 82.02821
[8] 91.44903 87.28444 97.25470 82.78518 81.28980 77.10442 82.14174
[15] -Inf 87.21062 88.85910 81.44612 82.62756 82.53242
> colMin(tmp5,na.rm=TRUE)
[1] 61.36191 64.92277 60.93760 64.87769 53.13773 55.10996 57.58947 56.09678
[9] 65.19576 54.15177 57.29754 56.93747 55.06896 59.18612 Inf 59.68132
[17] 57.76017 64.71903 60.28788 68.34726
>
>
>
>
> 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] 269.8402 209.2593 298.4653 203.6309 282.6385 202.2464 197.7000 238.8359
[9] 338.0595 88.1501
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 269.8402 209.2593 298.4653 203.6309 282.6385 202.2464 197.7000 238.8359
[9] 338.0595 88.1501
>
>
>
> 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] -5.684342e-14 -5.684342e-14 -1.421085e-14 -5.684342e-14 5.684342e-14
[6] 5.684342e-14 -7.105427e-14 -5.684342e-14 -2.842171e-14 -5.684342e-14
[11] 2.842171e-14 2.273737e-13 1.136868e-13 -8.526513e-14 5.684342e-14
[16] -1.705303e-13 -1.136868e-13 -2.842171e-14 0.000000e+00 0.000000e+00
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
4 13
8 15
5 1
2 14
1 17
9 12
1 11
2 3
1 8
1 18
1 13
4 15
7 3
2 7
5 18
8 18
8 6
1 20
4 20
2 7
There were 50 or more warnings (use warnings() to see the first 50)
>
>
> ### now test 1 by n and n by 1 matrix
>
>
> err.tol <- 1e-12
>
> rm(tmp5)
>
> dataset1 <- rnorm(100)
> dataset2 <- rnorm(100)
>
> tmp <- createBufferedMatrix(1,100)
> tmp[1,] <- dataset1
>
> tmp2 <- createBufferedMatrix(100,1)
> tmp2[,1] <- dataset2
>
>
>
>
>
> Max(tmp)
[1] 2.449493
> Min(tmp)
[1] -2.685792
> mean(tmp)
[1] -0.03431915
> Sum(tmp)
[1] -3.431915
> Var(tmp)
[1] 0.9300898
>
> rowMeans(tmp)
[1] -0.03431915
> rowSums(tmp)
[1] -3.431915
> rowVars(tmp)
[1] 0.9300898
> rowSd(tmp)
[1] 0.9644117
> rowMax(tmp)
[1] 2.449493
> rowMin(tmp)
[1] -2.685792
>
> colMeans(tmp)
[1] -0.896474681 0.848403334 -0.103532204 -0.925523067 -1.304793956
[6] 0.928495481 -0.758335783 -1.318139567 -0.055756089 1.090639778
[11] 1.438288717 1.036312596 -0.859249669 0.777540886 0.259802584
[16] -1.249514853 0.277409423 0.762865563 -1.595429311 0.634494839
[21] -0.832406295 1.539709388 -0.192610013 -2.142287323 -1.178741458
[26] 0.931345719 -0.010141781 1.231586398 -0.307550190 0.048899837
[31] 0.397946409 1.534292065 0.979682713 0.600898683 0.133094582
[36] 0.209020656 -0.558274539 -0.681828697 0.805227425 -0.380330849
[41] -0.925807678 -0.665993532 -0.453668732 -0.939437310 0.315521563
[46] -0.790596868 0.329372236 -0.242884841 -0.896269617 -0.534970040
[51] 0.245396407 -0.229229197 0.897027711 -0.847742118 -0.479715553
[56] -0.923007655 0.780950387 -0.866836141 -0.139585718 1.331066583
[61] 0.726997516 -0.040999402 -2.073620194 2.326967041 -1.875866918
[66] 1.076945407 -2.685791570 -0.519152964 1.521626966 0.189955016
[71] -0.574417817 0.492624539 1.014388469 0.972330497 -1.270643370
[76] -0.006620303 -0.380674243 -0.834407951 -0.715763697 -0.102757390
[81] 1.654136383 0.174339138 -0.024511784 -0.774772086 -0.971583920
[86] -0.150703559 -0.666460114 0.635337483 0.065613783 -0.414067285
[91] -0.706572839 -0.127397077 0.916469652 1.207053893 2.449492627
[96] -0.855495930 0.204094088 0.510073983 -0.730049256 0.853342047
> colSums(tmp)
[1] -0.896474681 0.848403334 -0.103532204 -0.925523067 -1.304793956
[6] 0.928495481 -0.758335783 -1.318139567 -0.055756089 1.090639778
[11] 1.438288717 1.036312596 -0.859249669 0.777540886 0.259802584
[16] -1.249514853 0.277409423 0.762865563 -1.595429311 0.634494839
[21] -0.832406295 1.539709388 -0.192610013 -2.142287323 -1.178741458
[26] 0.931345719 -0.010141781 1.231586398 -0.307550190 0.048899837
[31] 0.397946409 1.534292065 0.979682713 0.600898683 0.133094582
[36] 0.209020656 -0.558274539 -0.681828697 0.805227425 -0.380330849
[41] -0.925807678 -0.665993532 -0.453668732 -0.939437310 0.315521563
[46] -0.790596868 0.329372236 -0.242884841 -0.896269617 -0.534970040
[51] 0.245396407 -0.229229197 0.897027711 -0.847742118 -0.479715553
[56] -0.923007655 0.780950387 -0.866836141 -0.139585718 1.331066583
[61] 0.726997516 -0.040999402 -2.073620194 2.326967041 -1.875866918
[66] 1.076945407 -2.685791570 -0.519152964 1.521626966 0.189955016
[71] -0.574417817 0.492624539 1.014388469 0.972330497 -1.270643370
[76] -0.006620303 -0.380674243 -0.834407951 -0.715763697 -0.102757390
[81] 1.654136383 0.174339138 -0.024511784 -0.774772086 -0.971583920
[86] -0.150703559 -0.666460114 0.635337483 0.065613783 -0.414067285
[91] -0.706572839 -0.127397077 0.916469652 1.207053893 2.449492627
[96] -0.855495930 0.204094088 0.510073983 -0.730049256 0.853342047
> 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] -0.896474681 0.848403334 -0.103532204 -0.925523067 -1.304793956
[6] 0.928495481 -0.758335783 -1.318139567 -0.055756089 1.090639778
[11] 1.438288717 1.036312596 -0.859249669 0.777540886 0.259802584
[16] -1.249514853 0.277409423 0.762865563 -1.595429311 0.634494839
[21] -0.832406295 1.539709388 -0.192610013 -2.142287323 -1.178741458
[26] 0.931345719 -0.010141781 1.231586398 -0.307550190 0.048899837
[31] 0.397946409 1.534292065 0.979682713 0.600898683 0.133094582
[36] 0.209020656 -0.558274539 -0.681828697 0.805227425 -0.380330849
[41] -0.925807678 -0.665993532 -0.453668732 -0.939437310 0.315521563
[46] -0.790596868 0.329372236 -0.242884841 -0.896269617 -0.534970040
[51] 0.245396407 -0.229229197 0.897027711 -0.847742118 -0.479715553
[56] -0.923007655 0.780950387 -0.866836141 -0.139585718 1.331066583
[61] 0.726997516 -0.040999402 -2.073620194 2.326967041 -1.875866918
[66] 1.076945407 -2.685791570 -0.519152964 1.521626966 0.189955016
[71] -0.574417817 0.492624539 1.014388469 0.972330497 -1.270643370
[76] -0.006620303 -0.380674243 -0.834407951 -0.715763697 -0.102757390
[81] 1.654136383 0.174339138 -0.024511784 -0.774772086 -0.971583920
[86] -0.150703559 -0.666460114 0.635337483 0.065613783 -0.414067285
[91] -0.706572839 -0.127397077 0.916469652 1.207053893 2.449492627
[96] -0.855495930 0.204094088 0.510073983 -0.730049256 0.853342047
> colMin(tmp)
[1] -0.896474681 0.848403334 -0.103532204 -0.925523067 -1.304793956
[6] 0.928495481 -0.758335783 -1.318139567 -0.055756089 1.090639778
[11] 1.438288717 1.036312596 -0.859249669 0.777540886 0.259802584
[16] -1.249514853 0.277409423 0.762865563 -1.595429311 0.634494839
[21] -0.832406295 1.539709388 -0.192610013 -2.142287323 -1.178741458
[26] 0.931345719 -0.010141781 1.231586398 -0.307550190 0.048899837
[31] 0.397946409 1.534292065 0.979682713 0.600898683 0.133094582
[36] 0.209020656 -0.558274539 -0.681828697 0.805227425 -0.380330849
[41] -0.925807678 -0.665993532 -0.453668732 -0.939437310 0.315521563
[46] -0.790596868 0.329372236 -0.242884841 -0.896269617 -0.534970040
[51] 0.245396407 -0.229229197 0.897027711 -0.847742118 -0.479715553
[56] -0.923007655 0.780950387 -0.866836141 -0.139585718 1.331066583
[61] 0.726997516 -0.040999402 -2.073620194 2.326967041 -1.875866918
[66] 1.076945407 -2.685791570 -0.519152964 1.521626966 0.189955016
[71] -0.574417817 0.492624539 1.014388469 0.972330497 -1.270643370
[76] -0.006620303 -0.380674243 -0.834407951 -0.715763697 -0.102757390
[81] 1.654136383 0.174339138 -0.024511784 -0.774772086 -0.971583920
[86] -0.150703559 -0.666460114 0.635337483 0.065613783 -0.414067285
[91] -0.706572839 -0.127397077 0.916469652 1.207053893 2.449492627
[96] -0.855495930 0.204094088 0.510073983 -0.730049256 0.853342047
> colMedians(tmp)
[1] -0.896474681 0.848403334 -0.103532204 -0.925523067 -1.304793956
[6] 0.928495481 -0.758335783 -1.318139567 -0.055756089 1.090639778
[11] 1.438288717 1.036312596 -0.859249669 0.777540886 0.259802584
[16] -1.249514853 0.277409423 0.762865563 -1.595429311 0.634494839
[21] -0.832406295 1.539709388 -0.192610013 -2.142287323 -1.178741458
[26] 0.931345719 -0.010141781 1.231586398 -0.307550190 0.048899837
[31] 0.397946409 1.534292065 0.979682713 0.600898683 0.133094582
[36] 0.209020656 -0.558274539 -0.681828697 0.805227425 -0.380330849
[41] -0.925807678 -0.665993532 -0.453668732 -0.939437310 0.315521563
[46] -0.790596868 0.329372236 -0.242884841 -0.896269617 -0.534970040
[51] 0.245396407 -0.229229197 0.897027711 -0.847742118 -0.479715553
[56] -0.923007655 0.780950387 -0.866836141 -0.139585718 1.331066583
[61] 0.726997516 -0.040999402 -2.073620194 2.326967041 -1.875866918
[66] 1.076945407 -2.685791570 -0.519152964 1.521626966 0.189955016
[71] -0.574417817 0.492624539 1.014388469 0.972330497 -1.270643370
[76] -0.006620303 -0.380674243 -0.834407951 -0.715763697 -0.102757390
[81] 1.654136383 0.174339138 -0.024511784 -0.774772086 -0.971583920
[86] -0.150703559 -0.666460114 0.635337483 0.065613783 -0.414067285
[91] -0.706572839 -0.127397077 0.916469652 1.207053893 2.449492627
[96] -0.855495930 0.204094088 0.510073983 -0.730049256 0.853342047
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -0.8964747 0.8484033 -0.1035322 -0.9255231 -1.304794 0.9284955 -0.7583358
[2,] -0.8964747 0.8484033 -0.1035322 -0.9255231 -1.304794 0.9284955 -0.7583358
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -1.31814 -0.05575609 1.09064 1.438289 1.036313 -0.8592497 0.7775409
[2,] -1.31814 -0.05575609 1.09064 1.438289 1.036313 -0.8592497 0.7775409
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 0.2598026 -1.249515 0.2774094 0.7628656 -1.595429 0.6344948 -0.8324063
[2,] 0.2598026 -1.249515 0.2774094 0.7628656 -1.595429 0.6344948 -0.8324063
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 1.539709 -0.19261 -2.142287 -1.178741 0.9313457 -0.01014178 1.231586
[2,] 1.539709 -0.19261 -2.142287 -1.178741 0.9313457 -0.01014178 1.231586
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] -0.3075502 0.04889984 0.3979464 1.534292 0.9796827 0.6008987 0.1330946
[2,] -0.3075502 0.04889984 0.3979464 1.534292 0.9796827 0.6008987 0.1330946
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 0.2090207 -0.5582745 -0.6818287 0.8052274 -0.3803308 -0.9258077 -0.6659935
[2,] 0.2090207 -0.5582745 -0.6818287 0.8052274 -0.3803308 -0.9258077 -0.6659935
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.4536687 -0.9394373 0.3155216 -0.7905969 0.3293722 -0.2428848 -0.8962696
[2,] -0.4536687 -0.9394373 0.3155216 -0.7905969 0.3293722 -0.2428848 -0.8962696
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] -0.53497 0.2453964 -0.2292292 0.8970277 -0.8477421 -0.4797156 -0.9230077
[2,] -0.53497 0.2453964 -0.2292292 0.8970277 -0.8477421 -0.4797156 -0.9230077
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 0.7809504 -0.8668361 -0.1395857 1.331067 0.7269975 -0.0409994 -2.07362
[2,] 0.7809504 -0.8668361 -0.1395857 1.331067 0.7269975 -0.0409994 -2.07362
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 2.326967 -1.875867 1.076945 -2.685792 -0.519153 1.521627 0.189955
[2,] 2.326967 -1.875867 1.076945 -2.685792 -0.519153 1.521627 0.189955
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -0.5744178 0.4926245 1.014388 0.9723305 -1.270643 -0.006620303 -0.3806742
[2,] -0.5744178 0.4926245 1.014388 0.9723305 -1.270643 -0.006620303 -0.3806742
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -0.834408 -0.7157637 -0.1027574 1.654136 0.1743391 -0.02451178 -0.7747721
[2,] -0.834408 -0.7157637 -0.1027574 1.654136 0.1743391 -0.02451178 -0.7747721
[,85] [,86] [,87] [,88] [,89] [,90]
[1,] -0.9715839 -0.1507036 -0.6664601 0.6353375 0.06561378 -0.4140673
[2,] -0.9715839 -0.1507036 -0.6664601 0.6353375 0.06561378 -0.4140673
[,91] [,92] [,93] [,94] [,95] [,96] [,97]
[1,] -0.7065728 -0.1273971 0.9164697 1.207054 2.449493 -0.8554959 0.2040941
[2,] -0.7065728 -0.1273971 0.9164697 1.207054 2.449493 -0.8554959 0.2040941
[,98] [,99] [,100]
[1,] 0.510074 -0.7300493 0.853342
[2,] 0.510074 -0.7300493 0.853342
>
>
> Max(tmp2)
[1] 1.997532
> Min(tmp2)
[1] -1.891928
> mean(tmp2)
[1] -0.1382999
> Sum(tmp2)
[1] -13.82999
> Var(tmp2)
[1] 0.7819924
>
> rowMeans(tmp2)
[1] -1.78233588 -0.35177503 1.02641668 -0.35379968 -1.26728193 -1.00428328
[7] 0.34858993 0.17790088 1.53982560 -0.66604709 0.48649830 -1.86329755
[13] -1.72877617 -1.42396810 -1.81147838 0.51686376 1.36122201 -1.25133254
[19] 0.16382246 -0.13529699 -1.09221077 1.58129862 -0.56784493 -0.55820351
[25] 0.08110029 -0.16506415 1.59540344 1.04475143 0.21729515 -0.74621950
[31] 1.40133519 0.22543707 0.15762005 -1.17121748 0.50332739 -0.34674968
[37] 0.50646799 0.51606731 0.14405264 -0.15795292 0.86070813 0.92529177
[43] -0.47264599 0.38298515 -0.02023578 -0.13087455 0.48656758 0.91607266
[49] -1.89192822 -0.38964468 0.04517522 -0.64522106 0.21278529 0.79178904
[55] 0.10863159 -0.84906107 0.11358876 0.23597112 -0.81182298 0.02037556
[61] 0.29649419 -1.14797157 -1.11238133 -1.47003950 -0.44872337 -0.04623749
[67] 0.54523905 1.47931340 -0.86051559 -0.81464547 0.72343541 -0.39800372
[73] 0.05476529 0.45909958 0.23957304 0.42998461 -0.56181420 -0.39077602
[79] -0.95252164 -1.68736458 -1.25674587 -0.31000745 -0.87192979 -0.32472010
[85] -0.91128777 -0.07069007 0.13740201 0.85638260 0.46143597 -0.96026985
[91] -0.99058951 -1.58383258 1.99753167 0.45052890 -1.17402954 1.11586489
[97] 0.33898316 0.25537465 0.57818183 -0.94314722
> rowSums(tmp2)
[1] -1.78233588 -0.35177503 1.02641668 -0.35379968 -1.26728193 -1.00428328
[7] 0.34858993 0.17790088 1.53982560 -0.66604709 0.48649830 -1.86329755
[13] -1.72877617 -1.42396810 -1.81147838 0.51686376 1.36122201 -1.25133254
[19] 0.16382246 -0.13529699 -1.09221077 1.58129862 -0.56784493 -0.55820351
[25] 0.08110029 -0.16506415 1.59540344 1.04475143 0.21729515 -0.74621950
[31] 1.40133519 0.22543707 0.15762005 -1.17121748 0.50332739 -0.34674968
[37] 0.50646799 0.51606731 0.14405264 -0.15795292 0.86070813 0.92529177
[43] -0.47264599 0.38298515 -0.02023578 -0.13087455 0.48656758 0.91607266
[49] -1.89192822 -0.38964468 0.04517522 -0.64522106 0.21278529 0.79178904
[55] 0.10863159 -0.84906107 0.11358876 0.23597112 -0.81182298 0.02037556
[61] 0.29649419 -1.14797157 -1.11238133 -1.47003950 -0.44872337 -0.04623749
[67] 0.54523905 1.47931340 -0.86051559 -0.81464547 0.72343541 -0.39800372
[73] 0.05476529 0.45909958 0.23957304 0.42998461 -0.56181420 -0.39077602
[79] -0.95252164 -1.68736458 -1.25674587 -0.31000745 -0.87192979 -0.32472010
[85] -0.91128777 -0.07069007 0.13740201 0.85638260 0.46143597 -0.96026985
[91] -0.99058951 -1.58383258 1.99753167 0.45052890 -1.17402954 1.11586489
[97] 0.33898316 0.25537465 0.57818183 -0.94314722
> 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] -1.78233588 -0.35177503 1.02641668 -0.35379968 -1.26728193 -1.00428328
[7] 0.34858993 0.17790088 1.53982560 -0.66604709 0.48649830 -1.86329755
[13] -1.72877617 -1.42396810 -1.81147838 0.51686376 1.36122201 -1.25133254
[19] 0.16382246 -0.13529699 -1.09221077 1.58129862 -0.56784493 -0.55820351
[25] 0.08110029 -0.16506415 1.59540344 1.04475143 0.21729515 -0.74621950
[31] 1.40133519 0.22543707 0.15762005 -1.17121748 0.50332739 -0.34674968
[37] 0.50646799 0.51606731 0.14405264 -0.15795292 0.86070813 0.92529177
[43] -0.47264599 0.38298515 -0.02023578 -0.13087455 0.48656758 0.91607266
[49] -1.89192822 -0.38964468 0.04517522 -0.64522106 0.21278529 0.79178904
[55] 0.10863159 -0.84906107 0.11358876 0.23597112 -0.81182298 0.02037556
[61] 0.29649419 -1.14797157 -1.11238133 -1.47003950 -0.44872337 -0.04623749
[67] 0.54523905 1.47931340 -0.86051559 -0.81464547 0.72343541 -0.39800372
[73] 0.05476529 0.45909958 0.23957304 0.42998461 -0.56181420 -0.39077602
[79] -0.95252164 -1.68736458 -1.25674587 -0.31000745 -0.87192979 -0.32472010
[85] -0.91128777 -0.07069007 0.13740201 0.85638260 0.46143597 -0.96026985
[91] -0.99058951 -1.58383258 1.99753167 0.45052890 -1.17402954 1.11586489
[97] 0.33898316 0.25537465 0.57818183 -0.94314722
> rowMin(tmp2)
[1] -1.78233588 -0.35177503 1.02641668 -0.35379968 -1.26728193 -1.00428328
[7] 0.34858993 0.17790088 1.53982560 -0.66604709 0.48649830 -1.86329755
[13] -1.72877617 -1.42396810 -1.81147838 0.51686376 1.36122201 -1.25133254
[19] 0.16382246 -0.13529699 -1.09221077 1.58129862 -0.56784493 -0.55820351
[25] 0.08110029 -0.16506415 1.59540344 1.04475143 0.21729515 -0.74621950
[31] 1.40133519 0.22543707 0.15762005 -1.17121748 0.50332739 -0.34674968
[37] 0.50646799 0.51606731 0.14405264 -0.15795292 0.86070813 0.92529177
[43] -0.47264599 0.38298515 -0.02023578 -0.13087455 0.48656758 0.91607266
[49] -1.89192822 -0.38964468 0.04517522 -0.64522106 0.21278529 0.79178904
[55] 0.10863159 -0.84906107 0.11358876 0.23597112 -0.81182298 0.02037556
[61] 0.29649419 -1.14797157 -1.11238133 -1.47003950 -0.44872337 -0.04623749
[67] 0.54523905 1.47931340 -0.86051559 -0.81464547 0.72343541 -0.39800372
[73] 0.05476529 0.45909958 0.23957304 0.42998461 -0.56181420 -0.39077602
[79] -0.95252164 -1.68736458 -1.25674587 -0.31000745 -0.87192979 -0.32472010
[85] -0.91128777 -0.07069007 0.13740201 0.85638260 0.46143597 -0.96026985
[91] -0.99058951 -1.58383258 1.99753167 0.45052890 -1.17402954 1.11586489
[97] 0.33898316 0.25537465 0.57818183 -0.94314722
>
> colMeans(tmp2)
[1] -0.1382999
> colSums(tmp2)
[1] -13.82999
> colVars(tmp2)
[1] 0.7819924
> colSd(tmp2)
[1] 0.8843034
> colMax(tmp2)
[1] 1.997532
> colMin(tmp2)
[1] -1.891928
> colMedians(tmp2)
[1] -0.03323664
> colRanges(tmp2)
[,1]
[1,] -1.891928
[2,] 1.997532
>
> 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] 4.3070587 -1.1054273 1.2510224 -1.2714866 -0.1769240 -0.4185938
[7] 0.5632175 -1.9717737 -2.0860937 -4.4679238
> colApply(tmp,quantile)[,1]
[,1]
[1,] -2.6354746
[2,] -0.6093663
[3,] 0.7473405
[4,] 1.6823173
[5,] 2.1534991
>
> rowApply(tmp,sum)
[1] -0.7802659 -1.8297437 0.7925550 -0.1914169 1.3276882 -1.2547699
[7] 2.4776842 -6.8249338 -0.2791847 1.1854633
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 10 10 4 10 4 9 6 8 10
[2,] 4 4 7 7 9 5 4 4 9 1
[3,] 7 8 1 2 8 9 2 10 3 3
[4,] 8 5 9 8 3 8 1 7 2 5
[5,] 6 2 8 6 2 7 6 8 7 4
[6,] 5 9 6 5 5 3 10 5 10 2
[7,] 10 6 5 3 7 10 3 1 5 6
[8,] 3 7 2 1 4 1 5 9 6 9
[9,] 9 3 4 10 6 2 7 2 1 8
[10,] 2 1 3 9 1 6 8 3 4 7
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 2.5205409 -4.6486878 1.7033082 0.8408589 -2.2277815 -2.0786716
[7] -1.9698032 -0.8971124 0.3856300 0.2396651 -1.7781280 2.7742710
[13] -5.8558766 -4.3796791 2.2866348 1.6899803 3.1493922 4.2098767
[19] -1.3564430 -3.7442716
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.1028930
[2,] 0.2797344
[3,] 0.3333163
[4,] 0.3459403
[5,] 1.6644429
>
> rowApply(tmp,sum)
[1] 5.6197876 0.9218978 -7.9923210 -3.4937229 -4.1919381
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 10 20 16 12 12
[2,] 1 2 8 3 10
[3,] 18 8 11 19 8
[4,] 8 10 5 17 11
[5,] 20 6 7 14 1
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0.2797344 -1.1142036 1.32717927 0.2018453 1.9537651 -0.5538604
[2,] 1.6644429 -1.1625351 -0.08106364 0.1005695 -0.3951197 0.7826099
[3,] 0.3333163 -0.6970024 -0.56585955 -1.0729988 -0.8878900 -1.8915868
[4,] -0.1028930 -1.4611160 1.44909170 1.2958776 0.0588919 -0.7659101
[5,] 0.3459403 -0.2138306 -0.42603957 0.3155653 -2.9574288 0.3500758
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.73567083 0.8105861 -0.03432725 0.2476959 -0.8594905 1.02013510
[2,] 0.16396593 0.7422249 1.31582912 -0.2613387 -0.9500205 -0.05816669
[3,] -2.57230830 0.2854658 -1.83598987 -0.6331578 -0.9847952 2.11183789
[4,] -0.03463545 -1.5845602 2.04410466 0.4528246 0.4935964 -0.97854757
[5,] -0.26249621 -1.1508290 -1.10398662 0.4336411 0.5225817 0.67901227
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -0.7694099 0.3990728 1.7878998 -0.3040369 0.3841695 0.4507926
[2,] -0.8083932 -0.9346166 0.7557511 0.8435813 1.0175776 0.2028624
[3,] -0.2945413 -1.4436917 -0.0866066 -0.6429693 0.8918918 1.1489446
[4,] -2.1447309 -0.6955671 -0.9639705 -0.3173899 -0.1802343 1.3001048
[5,] -1.8388014 -1.7048765 0.7935609 2.1107951 1.0359877 1.1071722
[,19] [,20]
[1,] -0.8991969 0.55576632
[2,] 0.3120296 -2.32829247
[3,] 0.9453788 -0.09975851
[4,] -1.0279120 -0.33074765
[5,] -0.6867425 -1.54123928
>
>
> 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 : 649 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 : 562 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 0.3914957 0.2044079 0.1752931 -1.072384 1.593082 -0.9544304 0.5883245
col8 col9 col10 col11 col12 col13 col14
row1 -0.6195294 1.105155 -1.100473 -1.347613 -0.6636208 0.3645486 0.7512939
col15 col16 col17 col18 col19 col20
row1 -0.7281325 1.40188 0.4290291 0.4731742 -0.4511863 0.2621594
> tmp[,"col10"]
col10
row1 -1.1004728
row2 1.0758878
row3 -0.6039554
row4 1.5021798
row5 1.5643672
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 0.39149573 0.2044079 0.1752931 -1.0723837 1.5930816 -0.9544304
row5 -0.04803393 -0.1127656 -0.8267461 0.6552131 -0.5059579 -0.8051729
col7 col8 col9 col10 col11 col12
row1 0.5883245 -0.6195294 1.10515546 -1.100473 -1.3476127 -0.6636208
row5 0.3695283 -2.4315047 -0.01367348 1.564367 0.5035464 -2.0538244
col13 col14 col15 col16 col17 col18 col19
row1 0.3645486 0.7512939 -0.7281325 1.4018795 0.4290291 0.4731742 -0.4511863
row5 -0.2602846 0.9090912 -0.2747218 0.1601826 0.4951165 -0.4153219 -0.3290511
col20
row1 0.2621594
row5 0.1680099
> tmp[,c("col6","col20")]
col6 col20
row1 -0.9544304 0.2621594
row2 -0.7163792 0.4575405
row3 1.6962437 -2.6857001
row4 0.4345320 -2.5731750
row5 -0.8051729 0.1680099
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.9544304 0.2621594
row5 -0.8051729 0.1680099
>
>
>
>
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105)
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7 col8
row1 51.54921 50.33266 51.09856 48.90576 49.07451 104.4867 50.30271 49.00131
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.01373 49.73682 49.49871 51.09105 50.81253 51.19929 51.5962 47.95718
col17 col18 col19 col20
row1 50.63989 50.09649 51.19015 104.8116
> tmp[,"col10"]
col10
row1 49.73682
row2 30.62467
row3 31.41172
row4 30.14158
row5 49.87994
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 51.54921 50.33266 51.09856 48.90576 49.07451 104.4867 50.30271 49.00131
row5 51.26715 49.20436 51.49630 51.09682 49.33674 104.5248 51.00009 49.14508
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.01373 49.73682 49.49871 51.09105 50.81253 51.19929 51.59620 47.95718
row5 50.78968 49.87994 49.79645 50.06684 50.82389 50.09691 50.25044 50.65127
col17 col18 col19 col20
row1 50.63989 50.09649 51.19015 104.8116
row5 47.48884 49.86753 48.77568 105.4148
> tmp[,c("col6","col20")]
col6 col20
row1 104.48665 104.81161
row2 76.36303 75.83929
row3 74.66407 75.73796
row4 76.18183 72.81048
row5 104.52484 105.41482
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.4867 104.8116
row5 104.5248 105.4148
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.4867 104.8116
row5 104.5248 105.4148
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.33179573
[2,] 0.67764901
[3,] 0.62594127
[4,] -0.09824845
[5,] 1.01349305
> tmp[,c("col17","col7")]
col17 col7
[1,] 0.02094585 -1.6121664
[2,] 0.99485143 0.1510008
[3,] 0.37851645 1.3785600
[4,] 0.18487473 0.6380561
[5,] -1.74831053 2.4327650
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -1.82943289 0.1198586
[2,] 0.08883318 -0.1786875
[3,] -0.13840073 -0.8106906
[4,] -0.96971736 -0.4744447
[5,] 0.86924354 1.9047850
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -1.829433
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -1.82943289
[2,] 0.08883318
>
>
>
> 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 -1.5593542 0.5946017 0.4203288 -0.8376565 1.1134756 0.7761517 0.1579833
row1 0.5966549 -1.1836608 -0.7685776 -2.0144331 0.2153279 -0.9412431 0.4984014
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row3 -0.0846790 -0.8641314 0.06609554 0.9206397 0.7609034 0.7010642 -0.2146124
row1 -0.4066256 -0.9321793 1.67611291 0.2048214 1.4205702 0.8113697 -1.3377844
[,15] [,16] [,17] [,18] [,19] [,20]
row3 -0.8743239 -0.4258637 -0.19981938 0.9557065 0.8096210 1.0789016
row1 -0.7015591 0.1856771 -0.07423116 -0.3242001 -0.7175869 0.2242675
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 0.5869734 0.07775291 -1.367383 0.001226787 -2.482617 -0.1300483 0.4456459
[,8] [,9] [,10]
row2 -0.8403859 0.01216401 0.8404826
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 1.374313 -1.025271 1.212447 -0.2101212 1.191092 -0.7730937 0.6126637
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.7915757 0.3561089 -0.6897195 0.06601959 -0.5788664 0.5615594 2.329103
[,15] [,16] [,17] [,18] [,19] [,20]
row5 0.6360383 -0.2112118 0.154011 0.1364543 -0.405881 0.9087585
>
>
> 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: 0x30d113f0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM8f31c392958d3"
[2] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM8f31c45f0417"
[3] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM8f31c266c92c5"
[4] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM8f31c567ddbc3"
[5] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM8f31c45ad8ff6"
[6] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM8f31cb3f5372"
[7] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM8f31c459f97d1"
[8] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM8f31c7f153292"
[9] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM8f31c69788b96"
[10] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM8f31c26a25a30"
[11] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM8f31c1483385"
[12] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM8f31c1cd77aac"
[13] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM8f31c7683b5a3"
[14] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM8f31c38d04578"
[15] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM8f31c2acf6e4c"
>
>
> ### 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: 0x2ec83c00>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x2ec83c00>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x2ec83c00>
> rowMedians(tmp)
[1] 0.050783479 0.012491393 0.016001554 0.456666844 -0.210373696
[6] 0.365946972 0.347427258 0.273834637 -0.095298591 0.055045390
[11] -0.211413065 0.133188832 0.210526295 -0.085339659 0.077105929
[16] 0.217548598 0.110573012 -0.386243564 0.095682070 -0.021156254
[21] -0.164742868 0.285528461 0.051246289 -0.028542932 0.205789053
[26] 0.274270342 0.145185200 -0.656261304 0.602392440 -0.148497475
[31] 0.782105415 -0.521250133 -0.103746217 -0.354665041 0.112302176
[36] 0.018634995 -0.476450659 0.183519534 -0.019274086 -0.327021547
[41] 0.221478060 0.066890782 -0.129774093 0.025368606 0.288814835
[46] -0.166612502 -0.290944444 0.169453887 -0.344229831 -0.090972989
[51] -0.320127241 0.773919602 -0.044845115 -0.153168344 -0.159554681
[56] -0.111940708 0.339134283 -0.017217101 -0.436060368 -0.172755914
[61] -0.565965310 -0.574634515 -0.504799973 0.388245407 -0.188182896
[66] -0.084193761 0.142660036 -0.373849970 -0.211196348 -0.124550057
[71] 0.488044480 0.512923039 0.044962443 0.656386549 0.198885542
[76] 0.376959392 0.227491756 -0.241714071 0.592835899 0.377559854
[81] 0.009501843 0.311269910 0.324031648 0.211236903 -0.289045952
[86] 0.267042575 0.169272086 0.232974083 -0.126027769 -0.301146835
[91] 0.275050368 0.219432752 0.419503631 -0.670310440 0.185718693
[96] 0.047687756 0.137730329 -0.008011231 0.183269867 0.002392454
[101] -0.172842144 0.051904213 -0.219232284 0.442209430 -0.031448282
[106] -0.208925601 0.293070964 -0.553073713 0.382738229 -0.033117549
[111] 0.152405626 -0.484286323 -0.108458749 0.291980659 -0.136454741
[116] 0.251146562 -0.252331113 0.360650739 0.508941916 0.400176099
[121] -0.713897295 -0.190480045 0.157050300 0.413853192 -0.178632027
[126] 0.050257989 -0.199536505 -0.465738653 0.168366601 -0.117314284
[131] 0.528736788 0.195531598 -0.326963204 -0.488433292 -0.179586267
[136] 0.679336197 0.128787864 0.355721094 0.290383460 -0.148888562
[141] -0.212999678 -0.375618737 0.289394562 0.078143032 0.092818106
[146] 0.077680922 0.473445879 -0.754785223 -0.170977322 0.218865524
[151] 0.341453555 -0.042314535 0.473804546 0.042168573 -0.177413963
[156] -0.081594747 0.571657833 -0.506055038 0.075215674 -0.604250557
[161] 0.215018216 -0.095934201 0.272210348 -0.218009840 -0.245184501
[166] -0.513446051 0.056328119 -0.621476908 -0.271129886 -0.422389809
[171] -0.571655713 0.357481185 -0.176292469 0.016268645 -0.329409009
[176] -0.255789084 -0.228788805 -0.546937444 0.003236418 -0.612473671
[181] -0.017883909 0.090818710 0.081130542 0.390296524 0.198356171
[186] -0.165432892 -0.173433938 -0.413696142 0.202787879 -0.021016180
[191] 0.196625289 -0.282706016 -0.143192707 0.175225131 0.141831666
[196] 0.163423941 -0.493235638 -0.095986046 -0.335972782 -1.089195460
[201] -0.276977275 0.451831827 0.638662862 0.305289548 -0.603254413
[206] 0.078799285 -0.331463217 0.601091390 0.196167505 0.150586129
[211] 0.259882375 -0.029810416 0.081716674 -0.106855359 0.361307507
[216] 0.406788174 0.126959471 -0.517787408 -0.099565691 0.194205096
[221] 0.023384896 0.472749599 -0.366478615 0.147082837 -0.008325349
[226] 0.200936684 -0.067552270 0.041139698 -0.004129285 0.298392816
>
> proc.time()
user system elapsed
1.903 0.840 2.768
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: 0x2e1fbff0>
> .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: 0x2e1fbff0>
> .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: 0x2e1fbff0>
> .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: 0x2e1fbff0>
> 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: 0x2e106470>
> .Call("R_bm_AddColumn",P)
<pointer: 0x2e106470>
> .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: 0x2e106470>
> .Call("R_bm_AddColumn",P)
<pointer: 0x2e106470>
> .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: 0x2e106470>
> 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: 0x2e0e10e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x2e0e10e0>
> .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: 0x2e0e10e0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x2e0e10e0>
> .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: 0x2e0e10e0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x2e0e10e0>
> .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: 0x2e0e10e0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x2e0e10e0>
> .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: 0x2e0e10e0>
> 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: 0x2d068520>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x2d068520>
> .Call("R_bm_AddColumn",P)
<pointer: 0x2d068520>
> .Call("R_bm_AddColumn",P)
<pointer: 0x2d068520>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile8f363151f245" "BufferedMatrixFile8f36351499968"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile8f363151f245" "BufferedMatrixFile8f36351499968"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x2efb1030>
> .Call("R_bm_AddColumn",P)
<pointer: 0x2efb1030>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x2efb1030>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x2efb1030>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x2efb1030>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x2efb1030>
> .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: 0x2d97c5c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x2d97c5c0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x2d97c5c0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x2d97c5c0>
> 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: 0x2ea5cf30>
> .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: 0x2ea5cf30>
> rm(P)
>
> proc.time()
user system elapsed
0.345 0.038 0.368
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
0.310 0.059 0.355