Ben Bolstad
| Snapshot Date: 2025-08-29 13:45 -0400 (Fri, 29 Aug 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 2025-08-30 12:08 -0400 (Sat, 30 Aug 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 24.04.3 LTS) | x86_64 | 4.5.1 (2025-06-13) -- "Great Square Root" | 4824 |
| lconway | macOS 12.7.1 Monterey | x86_64 | 4.5.1 (2025-06-13) -- "Great Square Root" | 4615 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | 4.5.1 Patched (2025-06-14 r88325) -- "Great Square Root" | 4562 |
| taishan | Linux (openEuler 24.03 LTS) | aarch64 | 4.5.0 (2025-04-11) -- "How About a Twenty-Six" | 4541 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
| Package 252/2320 | 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: 2025-08-29 05:26:39 -0000 (Fri, 29 Aug 2025) |
| EndedAt: 2025-08-29 05:27:03 -0000 (Fri, 29 Aug 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
0.345 0.025 0.355
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] "Fri Aug 29 05:26:57 2025"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Fri Aug 29 05:26:57 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: 0x3a106ff0>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ which.col <- sample(1:20,1)
+ if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
>
>
> date()
[1] "Fri Aug 29 05:26:57 2025"
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
> date()
[1] "Fri Aug 29 05:26:57 2025"
>
> ColMode(tmp2)
<pointer: 0x3a106ff0>
>
>
>
> ### 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,] 100.9702852 -0.4027953 -0.3234038 -1.2446754
[2,] 2.4155811 -0.3874013 0.6454979 -0.6663700
[3,] 0.3870901 0.8969128 0.5742729 0.7210089
[4,] -1.5982790 -0.1927220 0.6108591 1.9504333
> 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,] 100.9702852 0.4027953 0.3234038 1.2446754
[2,] 2.4155811 0.3874013 0.6454979 0.6663700
[3,] 0.3870901 0.8969128 0.5742729 0.7210089
[4,] 1.5982790 0.1927220 0.6108591 1.9504333
> 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,] 10.0483971 0.6346615 0.5686861 1.1156502
[2,] 1.5542140 0.6224157 0.8034288 0.8163149
[3,] 0.6221656 0.9470548 0.7578079 0.8491224
[4,] 1.2642306 0.4390011 0.7815747 1.3965792
>
> 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,] 226.45426 31.74941 31.01026 37.40118
[2,] 42.95772 31.61156 33.67979 33.82952
[3,] 31.60875 35.36746 33.15235 34.21223
[4,] 39.24058 29.58273 33.42661 40.91622
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x3b3369a0>
> exp(tmp5)
<pointer: 0x3b3369a0>
> log(tmp5,2)
<pointer: 0x3b3369a0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 471.3349
> Min(tmp5)
[1] 52.49532
> mean(tmp5)
[1] 73.51759
> Sum(tmp5)
[1] 14703.52
> Var(tmp5)
[1] 877.9336
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 91.30243 71.45179 68.68115 74.52439 71.36956 72.35872 71.96860 69.90738
[9] 69.57946 74.03245
> rowSums(tmp5)
[1] 1826.049 1429.036 1373.623 1490.488 1427.391 1447.174 1439.372 1398.148
[9] 1391.589 1480.649
> rowVars(tmp5)
[1] 8075.53626 96.17066 83.80865 101.02198 48.81895 81.10969
[7] 74.51497 74.94071 51.96457 105.06420
> rowSd(tmp5)
[1] 89.863988 9.806664 9.154706 10.050969 6.987056 9.006092 8.632206
[8] 8.656830 7.208646 10.250083
> rowMax(tmp5)
[1] 471.33487 89.41087 88.49328 97.91980 84.39859 86.15215 88.11083
[8] 87.86748 80.73954 94.33239
> rowMin(tmp5)
[1] 60.10731 56.07764 52.49532 57.72284 58.99833 53.77603 55.09507 55.80413
[9] 56.08275 57.53384
>
> colMeans(tmp5)
[1] 112.17925 71.48336 69.37917 74.62324 74.07566 77.35994 70.61653
[8] 68.36632 68.39689 72.33773 74.13039 68.01757 69.71924 69.25088
[15] 71.80931 71.42537 67.50253 73.19692 72.76034 73.72119
> colSums(tmp5)
[1] 1121.7925 714.8336 693.7917 746.2324 740.7566 773.5994 706.1653
[8] 683.6632 683.9689 723.3773 741.3039 680.1757 697.1924 692.5088
[15] 718.0931 714.2537 675.0253 731.9692 727.6034 737.2119
> colVars(tmp5)
[1] 16024.22250 93.42529 25.30914 25.78730 64.32735 45.40166
[7] 63.30132 73.42014 161.48223 84.58779 119.39490 74.87494
[13] 46.15484 85.43770 79.85927 116.48203 101.43809 70.23779
[19] 60.20654 105.28883
> colSd(tmp5)
[1] 126.586818 9.665676 5.030819 5.078120 8.020433 6.738075
[7] 7.956213 8.568556 12.707566 9.197162 10.926797 8.653031
[13] 6.793735 9.243252 8.936402 10.792684 10.071648 8.380799
[19] 7.759287 10.261034
> colMax(tmp5)
[1] 471.33487 88.11083 81.91237 85.16176 87.86748 94.33239 80.58282
[8] 82.33909 93.09886 88.65938 97.91980 81.47200 80.53006 80.72317
[15] 88.49328 84.44743 82.36223 86.15215 84.14430 85.41588
> colMin(tmp5)
[1] 53.77603 57.67716 64.54380 67.86307 59.46039 69.67526 52.49532 56.07764
[9] 53.40664 57.60766 60.09437 55.80413 60.20907 56.50518 58.20284 56.08275
[17] 55.09507 63.72843 60.10731 54.66515
>
>
> ### 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] 91.30243 71.45179 68.68115 74.52439 71.36956 72.35872 71.96860 NA
[9] 69.57946 74.03245
> rowSums(tmp5)
[1] 1826.049 1429.036 1373.623 1490.488 1427.391 1447.174 1439.372 NA
[9] 1391.589 1480.649
> rowVars(tmp5)
[1] 8075.53626 96.17066 83.80865 101.02198 48.81895 81.10969
[7] 74.51497 77.23670 51.96457 105.06420
> rowSd(tmp5)
[1] 89.863988 9.806664 9.154706 10.050969 6.987056 9.006092 8.632206
[8] 8.788441 7.208646 10.250083
> rowMax(tmp5)
[1] 471.33487 89.41087 88.49328 97.91980 84.39859 86.15215 88.11083
[8] NA 80.73954 94.33239
> rowMin(tmp5)
[1] 60.10731 56.07764 52.49532 57.72284 58.99833 53.77603 55.09507 NA
[9] 56.08275 57.53384
>
> colMeans(tmp5)
[1] 112.17925 71.48336 69.37917 74.62324 74.07566 77.35994 70.61653
[8] 68.36632 68.39689 72.33773 74.13039 68.01757 69.71924 69.25088
[15] 71.80931 71.42537 67.50253 73.19692 NA 73.72119
> colSums(tmp5)
[1] 1121.7925 714.8336 693.7917 746.2324 740.7566 773.5994 706.1653
[8] 683.6632 683.9689 723.3773 741.3039 680.1757 697.1924 692.5088
[15] 718.0931 714.2537 675.0253 731.9692 NA 737.2119
> colVars(tmp5)
[1] 16024.22250 93.42529 25.30914 25.78730 64.32735 45.40166
[7] 63.30132 73.42014 161.48223 84.58779 119.39490 74.87494
[13] 46.15484 85.43770 79.85927 116.48203 101.43809 70.23779
[19] NA 105.28883
> colSd(tmp5)
[1] 126.586818 9.665676 5.030819 5.078120 8.020433 6.738075
[7] 7.956213 8.568556 12.707566 9.197162 10.926797 8.653031
[13] 6.793735 9.243252 8.936402 10.792684 10.071648 8.380799
[19] NA 10.261034
> colMax(tmp5)
[1] 471.33487 88.11083 81.91237 85.16176 87.86748 94.33239 80.58282
[8] 82.33909 93.09886 88.65938 97.91980 81.47200 80.53006 80.72317
[15] 88.49328 84.44743 82.36223 86.15215 NA 85.41588
> colMin(tmp5)
[1] 53.77603 57.67716 64.54380 67.86307 59.46039 69.67526 52.49532 56.07764
[9] 53.40664 57.60766 60.09437 55.80413 60.20907 56.50518 58.20284 56.08275
[17] 55.09507 63.72843 NA 54.66515
>
> Max(tmp5,na.rm=TRUE)
[1] 471.3349
> Min(tmp5,na.rm=TRUE)
[1] 52.49532
> mean(tmp5,na.rm=TRUE)
[1] 73.56413
> Sum(tmp5,na.rm=TRUE)
[1] 14639.26
> Var(tmp5,na.rm=TRUE)
[1] 881.9323
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.30243 71.45179 68.68115 74.52439 71.36956 72.35872 71.96860 70.20480
[9] 69.57946 74.03245
> rowSums(tmp5,na.rm=TRUE)
[1] 1826.049 1429.036 1373.623 1490.488 1427.391 1447.174 1439.372 1333.891
[9] 1391.589 1480.649
> rowVars(tmp5,na.rm=TRUE)
[1] 8075.53626 96.17066 83.80865 101.02198 48.81895 81.10969
[7] 74.51497 77.23670 51.96457 105.06420
> rowSd(tmp5,na.rm=TRUE)
[1] 89.863988 9.806664 9.154706 10.050969 6.987056 9.006092 8.632206
[8] 8.788441 7.208646 10.250083
> rowMax(tmp5,na.rm=TRUE)
[1] 471.33487 89.41087 88.49328 97.91980 84.39859 86.15215 88.11083
[8] 87.86748 80.73954 94.33239
> rowMin(tmp5,na.rm=TRUE)
[1] 60.10731 56.07764 52.49532 57.72284 58.99833 53.77603 55.09507 55.80413
[9] 56.08275 57.53384
>
> colMeans(tmp5,na.rm=TRUE)
[1] 112.17925 71.48336 69.37917 74.62324 74.07566 77.35994 70.61653
[8] 68.36632 68.39689 72.33773 74.13039 68.01757 69.71924 69.25088
[15] 71.80931 71.42537 67.50253 73.19692 73.70521 73.72119
> colSums(tmp5,na.rm=TRUE)
[1] 1121.7925 714.8336 693.7917 746.2324 740.7566 773.5994 706.1653
[8] 683.6632 683.9689 723.3773 741.3039 680.1757 697.1924 692.5088
[15] 718.0931 714.2537 675.0253 731.9692 663.3469 737.2119
> colVars(tmp5,na.rm=TRUE)
[1] 16024.22250 93.42529 25.30914 25.78730 64.32735 45.40166
[7] 63.30132 73.42014 161.48223 84.58779 119.39490 74.87494
[13] 46.15484 85.43770 79.85927 116.48203 101.43809 70.23779
[19] 57.68861 105.28883
> colSd(tmp5,na.rm=TRUE)
[1] 126.586818 9.665676 5.030819 5.078120 8.020433 6.738075
[7] 7.956213 8.568556 12.707566 9.197162 10.926797 8.653031
[13] 6.793735 9.243252 8.936402 10.792684 10.071648 8.380799
[19] 7.595302 10.261034
> colMax(tmp5,na.rm=TRUE)
[1] 471.33487 88.11083 81.91237 85.16176 87.86748 94.33239 80.58282
[8] 82.33909 93.09886 88.65938 97.91980 81.47200 80.53006 80.72317
[15] 88.49328 84.44743 82.36223 86.15215 84.14430 85.41588
> colMin(tmp5,na.rm=TRUE)
[1] 53.77603 57.67716 64.54380 67.86307 59.46039 69.67526 52.49532 56.07764
[9] 53.40664 57.60766 60.09437 55.80413 60.20907 56.50518 58.20284 56.08275
[17] 55.09507 63.72843 60.10731 54.66515
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.30243 71.45179 68.68115 74.52439 71.36956 72.35872 71.96860 NaN
[9] 69.57946 74.03245
> rowSums(tmp5,na.rm=TRUE)
[1] 1826.049 1429.036 1373.623 1490.488 1427.391 1447.174 1439.372 0.000
[9] 1391.589 1480.649
> rowVars(tmp5,na.rm=TRUE)
[1] 8075.53626 96.17066 83.80865 101.02198 48.81895 81.10969
[7] 74.51497 NA 51.96457 105.06420
> rowSd(tmp5,na.rm=TRUE)
[1] 89.863988 9.806664 9.154706 10.050969 6.987056 9.006092 8.632206
[8] NA 7.208646 10.250083
> rowMax(tmp5,na.rm=TRUE)
[1] 471.33487 89.41087 88.49328 97.91980 84.39859 86.15215 88.11083
[8] NA 80.73954 94.33239
> rowMin(tmp5,na.rm=TRUE)
[1] 60.10731 56.07764 52.49532 57.72284 58.99833 53.77603 55.09507 NA
[9] 56.08275 57.53384
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 117.67606 73.01739 69.77401 75.37437 72.54323 77.53357 69.50916
[8] 67.44947 69.37858 72.56485 74.28672 69.37462 69.84290 69.18028
[15] 71.63018 70.23836 68.52267 73.30172 NaN 73.47116
> colSums(tmp5,na.rm=TRUE)
[1] 1059.0845 657.1565 627.9661 678.3693 652.8891 697.8021 625.5824
[8] 607.0452 624.4072 653.0836 668.5804 624.3716 628.5861 622.6225
[15] 644.6716 632.1453 616.7041 659.7155 0.0000 661.2405
> colVars(tmp5,na.rm=TRUE)
[1] 17687.33276 78.62964 26.71890 22.66351 45.94961 50.73772
[7] 57.41858 73.14073 170.82583 94.58098 134.04432 63.51652
[13] 51.75215 96.06135 89.48071 115.19107 102.41014 78.89394
[19] NA 117.74664
> colSd(tmp5,na.rm=TRUE)
[1] 132.993732 8.867336 5.169032 4.760621 6.778614 7.123042
[7] 7.577505 8.552236 13.070036 9.725275 11.577751 7.969725
[13] 7.193897 9.801089 9.459424 10.732710 10.119790 8.882226
[19] NA 10.851112
> colMax(tmp5,na.rm=TRUE)
[1] 471.33487 88.11083 81.91237 85.16176 81.65282 94.33239 77.75140
[8] 82.33909 93.09886 88.65938 97.91980 81.47200 80.53006 80.72317
[15] 88.49328 84.44743 82.36223 86.15215 -Inf 85.41588
> colMin(tmp5,na.rm=TRUE)
[1] 53.77603 61.57258 64.54380 70.41171 59.46039 69.67526 52.49532 56.07764
[9] 53.40664 57.60766 60.09437 57.53384 60.20907 56.50518 58.20284 56.08275
[17] 55.09507 63.72843 Inf 54.66515
>
>
>
>
> 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] 314.6433 234.8660 293.5709 220.5890 182.6216 283.3278 157.0029 345.4982
[9] 122.5851 171.1696
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 314.6433 234.8660 293.5709 220.5890 182.6216 283.3278 157.0029 345.4982
[9] 122.5851 171.1696
>
>
>
> 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] -2.842171e-14 1.705303e-13 4.263256e-13 -2.842171e-14 0.000000e+00
[6] 4.547474e-13 5.684342e-14 4.973799e-14 -8.526513e-14 -1.705303e-13
[11] 5.684342e-14 2.273737e-13 -5.684342e-14 -2.842171e-14 -1.705303e-13
[16] -1.136868e-13 -5.684342e-14 4.263256e-14 2.842171e-14 -5.684342e-14
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
4 2
6 2
4 7
4 9
1 13
5 9
5 15
8 3
9 8
7 1
7 4
7 17
6 10
6 1
8 10
2 8
9 11
4 20
1 1
9 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] 2.602794
> Min(tmp)
[1] -2.717506
> mean(tmp)
[1] 0.03653372
> Sum(tmp)
[1] 3.653372
> Var(tmp)
[1] 1.144036
>
> rowMeans(tmp)
[1] 0.03653372
> rowSums(tmp)
[1] 3.653372
> rowVars(tmp)
[1] 1.144036
> rowSd(tmp)
[1] 1.069596
> rowMax(tmp)
[1] 2.602794
> rowMin(tmp)
[1] -2.717506
>
> colMeans(tmp)
[1] 1.46729786 0.59565999 0.42010065 0.95749302 0.31161915 -0.46401055
[7] -0.09444092 -0.07049752 -1.19811056 -0.17254514 0.09854990 -1.09944830
[13] -0.10205499 -2.34623991 -0.87388616 1.80606926 0.00289454 -1.67065407
[19] -0.20448799 -2.15414701 1.28215098 1.13169323 -0.88767927 -0.62666299
[25] -0.47126159 -2.57334751 0.83961990 1.47476874 1.00926443 -0.64740862
[31] 0.06663147 1.07558892 0.97516335 -1.16661224 -0.46366767 0.06453976
[37] -0.16789814 0.97055468 0.88101762 -1.18879118 1.11761899 0.49239801
[43] 0.04870263 1.21144733 -0.75307935 -0.56030754 1.20421254 -1.17877590
[49] 1.00542021 0.80536834 -0.53634449 -1.23320360 -0.61605165 1.23638999
[55] -0.30917134 0.87697766 -0.43312661 0.39763158 0.22818337 0.66224837
[61] 0.28015868 1.12241172 1.24880048 0.83123459 0.56082026 -0.45962211
[67] 0.76710793 0.28889640 1.50293437 0.96026393 -2.44401208 -0.88664115
[73] -0.11303255 -0.21040855 0.36423757 0.47242135 1.93547246 -0.24972808
[79] -1.21113690 -1.16018826 -0.15315807 -1.16645457 -0.67881467 0.31994719
[85] 1.64950621 -0.00680108 -0.80628485 0.18549351 2.60279446 -1.94514682
[91] 0.19123374 1.63036278 0.64283622 0.86379384 -0.62289733 1.71183458
[97] -2.71750635 -0.88568816 -0.87002971 -0.34500296
> colSums(tmp)
[1] 1.46729786 0.59565999 0.42010065 0.95749302 0.31161915 -0.46401055
[7] -0.09444092 -0.07049752 -1.19811056 -0.17254514 0.09854990 -1.09944830
[13] -0.10205499 -2.34623991 -0.87388616 1.80606926 0.00289454 -1.67065407
[19] -0.20448799 -2.15414701 1.28215098 1.13169323 -0.88767927 -0.62666299
[25] -0.47126159 -2.57334751 0.83961990 1.47476874 1.00926443 -0.64740862
[31] 0.06663147 1.07558892 0.97516335 -1.16661224 -0.46366767 0.06453976
[37] -0.16789814 0.97055468 0.88101762 -1.18879118 1.11761899 0.49239801
[43] 0.04870263 1.21144733 -0.75307935 -0.56030754 1.20421254 -1.17877590
[49] 1.00542021 0.80536834 -0.53634449 -1.23320360 -0.61605165 1.23638999
[55] -0.30917134 0.87697766 -0.43312661 0.39763158 0.22818337 0.66224837
[61] 0.28015868 1.12241172 1.24880048 0.83123459 0.56082026 -0.45962211
[67] 0.76710793 0.28889640 1.50293437 0.96026393 -2.44401208 -0.88664115
[73] -0.11303255 -0.21040855 0.36423757 0.47242135 1.93547246 -0.24972808
[79] -1.21113690 -1.16018826 -0.15315807 -1.16645457 -0.67881467 0.31994719
[85] 1.64950621 -0.00680108 -0.80628485 0.18549351 2.60279446 -1.94514682
[91] 0.19123374 1.63036278 0.64283622 0.86379384 -0.62289733 1.71183458
[97] -2.71750635 -0.88568816 -0.87002971 -0.34500296
> 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] 1.46729786 0.59565999 0.42010065 0.95749302 0.31161915 -0.46401055
[7] -0.09444092 -0.07049752 -1.19811056 -0.17254514 0.09854990 -1.09944830
[13] -0.10205499 -2.34623991 -0.87388616 1.80606926 0.00289454 -1.67065407
[19] -0.20448799 -2.15414701 1.28215098 1.13169323 -0.88767927 -0.62666299
[25] -0.47126159 -2.57334751 0.83961990 1.47476874 1.00926443 -0.64740862
[31] 0.06663147 1.07558892 0.97516335 -1.16661224 -0.46366767 0.06453976
[37] -0.16789814 0.97055468 0.88101762 -1.18879118 1.11761899 0.49239801
[43] 0.04870263 1.21144733 -0.75307935 -0.56030754 1.20421254 -1.17877590
[49] 1.00542021 0.80536834 -0.53634449 -1.23320360 -0.61605165 1.23638999
[55] -0.30917134 0.87697766 -0.43312661 0.39763158 0.22818337 0.66224837
[61] 0.28015868 1.12241172 1.24880048 0.83123459 0.56082026 -0.45962211
[67] 0.76710793 0.28889640 1.50293437 0.96026393 -2.44401208 -0.88664115
[73] -0.11303255 -0.21040855 0.36423757 0.47242135 1.93547246 -0.24972808
[79] -1.21113690 -1.16018826 -0.15315807 -1.16645457 -0.67881467 0.31994719
[85] 1.64950621 -0.00680108 -0.80628485 0.18549351 2.60279446 -1.94514682
[91] 0.19123374 1.63036278 0.64283622 0.86379384 -0.62289733 1.71183458
[97] -2.71750635 -0.88568816 -0.87002971 -0.34500296
> colMin(tmp)
[1] 1.46729786 0.59565999 0.42010065 0.95749302 0.31161915 -0.46401055
[7] -0.09444092 -0.07049752 -1.19811056 -0.17254514 0.09854990 -1.09944830
[13] -0.10205499 -2.34623991 -0.87388616 1.80606926 0.00289454 -1.67065407
[19] -0.20448799 -2.15414701 1.28215098 1.13169323 -0.88767927 -0.62666299
[25] -0.47126159 -2.57334751 0.83961990 1.47476874 1.00926443 -0.64740862
[31] 0.06663147 1.07558892 0.97516335 -1.16661224 -0.46366767 0.06453976
[37] -0.16789814 0.97055468 0.88101762 -1.18879118 1.11761899 0.49239801
[43] 0.04870263 1.21144733 -0.75307935 -0.56030754 1.20421254 -1.17877590
[49] 1.00542021 0.80536834 -0.53634449 -1.23320360 -0.61605165 1.23638999
[55] -0.30917134 0.87697766 -0.43312661 0.39763158 0.22818337 0.66224837
[61] 0.28015868 1.12241172 1.24880048 0.83123459 0.56082026 -0.45962211
[67] 0.76710793 0.28889640 1.50293437 0.96026393 -2.44401208 -0.88664115
[73] -0.11303255 -0.21040855 0.36423757 0.47242135 1.93547246 -0.24972808
[79] -1.21113690 -1.16018826 -0.15315807 -1.16645457 -0.67881467 0.31994719
[85] 1.64950621 -0.00680108 -0.80628485 0.18549351 2.60279446 -1.94514682
[91] 0.19123374 1.63036278 0.64283622 0.86379384 -0.62289733 1.71183458
[97] -2.71750635 -0.88568816 -0.87002971 -0.34500296
> colMedians(tmp)
[1] 1.46729786 0.59565999 0.42010065 0.95749302 0.31161915 -0.46401055
[7] -0.09444092 -0.07049752 -1.19811056 -0.17254514 0.09854990 -1.09944830
[13] -0.10205499 -2.34623991 -0.87388616 1.80606926 0.00289454 -1.67065407
[19] -0.20448799 -2.15414701 1.28215098 1.13169323 -0.88767927 -0.62666299
[25] -0.47126159 -2.57334751 0.83961990 1.47476874 1.00926443 -0.64740862
[31] 0.06663147 1.07558892 0.97516335 -1.16661224 -0.46366767 0.06453976
[37] -0.16789814 0.97055468 0.88101762 -1.18879118 1.11761899 0.49239801
[43] 0.04870263 1.21144733 -0.75307935 -0.56030754 1.20421254 -1.17877590
[49] 1.00542021 0.80536834 -0.53634449 -1.23320360 -0.61605165 1.23638999
[55] -0.30917134 0.87697766 -0.43312661 0.39763158 0.22818337 0.66224837
[61] 0.28015868 1.12241172 1.24880048 0.83123459 0.56082026 -0.45962211
[67] 0.76710793 0.28889640 1.50293437 0.96026393 -2.44401208 -0.88664115
[73] -0.11303255 -0.21040855 0.36423757 0.47242135 1.93547246 -0.24972808
[79] -1.21113690 -1.16018826 -0.15315807 -1.16645457 -0.67881467 0.31994719
[85] 1.64950621 -0.00680108 -0.80628485 0.18549351 2.60279446 -1.94514682
[91] 0.19123374 1.63036278 0.64283622 0.86379384 -0.62289733 1.71183458
[97] -2.71750635 -0.88568816 -0.87002971 -0.34500296
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 1.467298 0.59566 0.4201006 0.957493 0.3116191 -0.4640105 -0.09444092
[2,] 1.467298 0.59566 0.4201006 0.957493 0.3116191 -0.4640105 -0.09444092
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] -0.07049752 -1.198111 -0.1725451 0.0985499 -1.099448 -0.102055 -2.34624
[2,] -0.07049752 -1.198111 -0.1725451 0.0985499 -1.099448 -0.102055 -2.34624
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -0.8738862 1.806069 0.00289454 -1.670654 -0.204488 -2.154147 1.282151
[2,] -0.8738862 1.806069 0.00289454 -1.670654 -0.204488 -2.154147 1.282151
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 1.131693 -0.8876793 -0.626663 -0.4712616 -2.573348 0.8396199 1.474769
[2,] 1.131693 -0.8876793 -0.626663 -0.4712616 -2.573348 0.8396199 1.474769
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 1.009264 -0.6474086 0.06663147 1.075589 0.9751633 -1.166612 -0.4636677
[2,] 1.009264 -0.6474086 0.06663147 1.075589 0.9751633 -1.166612 -0.4636677
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 0.06453976 -0.1678981 0.9705547 0.8810176 -1.188791 1.117619 0.492398
[2,] 0.06453976 -0.1678981 0.9705547 0.8810176 -1.188791 1.117619 0.492398
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] 0.04870263 1.211447 -0.7530793 -0.5603075 1.204213 -1.178776 1.00542
[2,] 0.04870263 1.211447 -0.7530793 -0.5603075 1.204213 -1.178776 1.00542
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 0.8053683 -0.5363445 -1.233204 -0.6160517 1.23639 -0.3091713 0.8769777
[2,] 0.8053683 -0.5363445 -1.233204 -0.6160517 1.23639 -0.3091713 0.8769777
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] -0.4331266 0.3976316 0.2281834 0.6622484 0.2801587 1.122412 1.2488
[2,] -0.4331266 0.3976316 0.2281834 0.6622484 0.2801587 1.122412 1.2488
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 0.8312346 0.5608203 -0.4596221 0.7671079 0.2888964 1.502934 0.9602639
[2,] 0.8312346 0.5608203 -0.4596221 0.7671079 0.2888964 1.502934 0.9602639
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -2.444012 -0.8866412 -0.1130325 -0.2104086 0.3642376 0.4724214 1.935472
[2,] -2.444012 -0.8866412 -0.1130325 -0.2104086 0.3642376 0.4724214 1.935472
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -0.2497281 -1.211137 -1.160188 -0.1531581 -1.166455 -0.6788147 0.3199472
[2,] -0.2497281 -1.211137 -1.160188 -0.1531581 -1.166455 -0.6788147 0.3199472
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 1.649506 -0.00680108 -0.8062848 0.1854935 2.602794 -1.945147 0.1912337
[2,] 1.649506 -0.00680108 -0.8062848 0.1854935 2.602794 -1.945147 0.1912337
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] 1.630363 0.6428362 0.8637938 -0.6228973 1.711835 -2.717506 -0.8856882
[2,] 1.630363 0.6428362 0.8637938 -0.6228973 1.711835 -2.717506 -0.8856882
[,99] [,100]
[1,] -0.8700297 -0.345003
[2,] -0.8700297 -0.345003
>
>
> Max(tmp2)
[1] 2.735577
> Min(tmp2)
[1] -2.975244
> mean(tmp2)
[1] -0.03351325
> Sum(tmp2)
[1] -3.351325
> Var(tmp2)
[1] 0.9361805
>
> rowMeans(tmp2)
[1] -0.70058514 -0.18033264 0.01589911 -0.78643424 0.44191583 -0.32080238
[7] 1.06247448 -0.12685038 -0.35472300 0.96877695 1.08231302 -0.14714595
[13] -0.12841099 0.12621273 -0.59605847 -1.57099597 -0.13906765 0.34811725
[19] 1.02688175 -0.92628932 0.89010204 0.27321614 -2.97524448 -1.67485096
[25] 0.82980928 0.83134610 -1.14541957 -0.08706863 -1.74969166 1.06750121
[31] 0.19289805 1.30949834 -0.55196393 -2.28037769 0.04396691 0.30393819
[37] 0.41015514 -0.36584660 0.64303164 -0.57564595 0.09228936 1.86407208
[43] 1.25304384 0.92260145 -0.51241473 0.10040434 0.08226978 0.37753930
[49] -0.93925184 -1.08235708 -1.09472622 0.51438085 0.01190140 -0.64330673
[55] 1.46526834 0.35501437 0.80420166 -0.26868984 -0.77157576 -1.15022375
[61] 0.10893927 -1.70987653 1.63111838 0.79379268 -1.14709377 0.62250745
[67] 0.31901432 -1.58631914 -1.10175183 0.23524455 -0.46517440 -0.16937891
[73] 0.38619015 1.40322537 -2.26441615 -0.53150377 0.78950118 0.88975967
[79] -0.27954647 -0.22792956 -0.79826431 -0.89401554 1.75500364 -0.81834731
[85] 1.62386235 0.39042311 -0.49149314 0.32081761 0.41699789 0.61580680
[91] 0.08792267 -0.62313241 -0.53839262 -0.06668871 0.78590774 -0.58853840
[97] -0.28154055 0.31064107 2.73557737 -0.85486466
> rowSums(tmp2)
[1] -0.70058514 -0.18033264 0.01589911 -0.78643424 0.44191583 -0.32080238
[7] 1.06247448 -0.12685038 -0.35472300 0.96877695 1.08231302 -0.14714595
[13] -0.12841099 0.12621273 -0.59605847 -1.57099597 -0.13906765 0.34811725
[19] 1.02688175 -0.92628932 0.89010204 0.27321614 -2.97524448 -1.67485096
[25] 0.82980928 0.83134610 -1.14541957 -0.08706863 -1.74969166 1.06750121
[31] 0.19289805 1.30949834 -0.55196393 -2.28037769 0.04396691 0.30393819
[37] 0.41015514 -0.36584660 0.64303164 -0.57564595 0.09228936 1.86407208
[43] 1.25304384 0.92260145 -0.51241473 0.10040434 0.08226978 0.37753930
[49] -0.93925184 -1.08235708 -1.09472622 0.51438085 0.01190140 -0.64330673
[55] 1.46526834 0.35501437 0.80420166 -0.26868984 -0.77157576 -1.15022375
[61] 0.10893927 -1.70987653 1.63111838 0.79379268 -1.14709377 0.62250745
[67] 0.31901432 -1.58631914 -1.10175183 0.23524455 -0.46517440 -0.16937891
[73] 0.38619015 1.40322537 -2.26441615 -0.53150377 0.78950118 0.88975967
[79] -0.27954647 -0.22792956 -0.79826431 -0.89401554 1.75500364 -0.81834731
[85] 1.62386235 0.39042311 -0.49149314 0.32081761 0.41699789 0.61580680
[91] 0.08792267 -0.62313241 -0.53839262 -0.06668871 0.78590774 -0.58853840
[97] -0.28154055 0.31064107 2.73557737 -0.85486466
> 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] -0.70058514 -0.18033264 0.01589911 -0.78643424 0.44191583 -0.32080238
[7] 1.06247448 -0.12685038 -0.35472300 0.96877695 1.08231302 -0.14714595
[13] -0.12841099 0.12621273 -0.59605847 -1.57099597 -0.13906765 0.34811725
[19] 1.02688175 -0.92628932 0.89010204 0.27321614 -2.97524448 -1.67485096
[25] 0.82980928 0.83134610 -1.14541957 -0.08706863 -1.74969166 1.06750121
[31] 0.19289805 1.30949834 -0.55196393 -2.28037769 0.04396691 0.30393819
[37] 0.41015514 -0.36584660 0.64303164 -0.57564595 0.09228936 1.86407208
[43] 1.25304384 0.92260145 -0.51241473 0.10040434 0.08226978 0.37753930
[49] -0.93925184 -1.08235708 -1.09472622 0.51438085 0.01190140 -0.64330673
[55] 1.46526834 0.35501437 0.80420166 -0.26868984 -0.77157576 -1.15022375
[61] 0.10893927 -1.70987653 1.63111838 0.79379268 -1.14709377 0.62250745
[67] 0.31901432 -1.58631914 -1.10175183 0.23524455 -0.46517440 -0.16937891
[73] 0.38619015 1.40322537 -2.26441615 -0.53150377 0.78950118 0.88975967
[79] -0.27954647 -0.22792956 -0.79826431 -0.89401554 1.75500364 -0.81834731
[85] 1.62386235 0.39042311 -0.49149314 0.32081761 0.41699789 0.61580680
[91] 0.08792267 -0.62313241 -0.53839262 -0.06668871 0.78590774 -0.58853840
[97] -0.28154055 0.31064107 2.73557737 -0.85486466
> rowMin(tmp2)
[1] -0.70058514 -0.18033264 0.01589911 -0.78643424 0.44191583 -0.32080238
[7] 1.06247448 -0.12685038 -0.35472300 0.96877695 1.08231302 -0.14714595
[13] -0.12841099 0.12621273 -0.59605847 -1.57099597 -0.13906765 0.34811725
[19] 1.02688175 -0.92628932 0.89010204 0.27321614 -2.97524448 -1.67485096
[25] 0.82980928 0.83134610 -1.14541957 -0.08706863 -1.74969166 1.06750121
[31] 0.19289805 1.30949834 -0.55196393 -2.28037769 0.04396691 0.30393819
[37] 0.41015514 -0.36584660 0.64303164 -0.57564595 0.09228936 1.86407208
[43] 1.25304384 0.92260145 -0.51241473 0.10040434 0.08226978 0.37753930
[49] -0.93925184 -1.08235708 -1.09472622 0.51438085 0.01190140 -0.64330673
[55] 1.46526834 0.35501437 0.80420166 -0.26868984 -0.77157576 -1.15022375
[61] 0.10893927 -1.70987653 1.63111838 0.79379268 -1.14709377 0.62250745
[67] 0.31901432 -1.58631914 -1.10175183 0.23524455 -0.46517440 -0.16937891
[73] 0.38619015 1.40322537 -2.26441615 -0.53150377 0.78950118 0.88975967
[79] -0.27954647 -0.22792956 -0.79826431 -0.89401554 1.75500364 -0.81834731
[85] 1.62386235 0.39042311 -0.49149314 0.32081761 0.41699789 0.61580680
[91] 0.08792267 -0.62313241 -0.53839262 -0.06668871 0.78590774 -0.58853840
[97] -0.28154055 0.31064107 2.73557737 -0.85486466
>
> colMeans(tmp2)
[1] -0.03351325
> colSums(tmp2)
[1] -3.351325
> colVars(tmp2)
[1] 0.9361805
> colSd(tmp2)
[1] 0.9675642
> colMax(tmp2)
[1] 2.735577
> colMin(tmp2)
[1] -2.975244
> colMedians(tmp2)
[1] 0.01390026
> colRanges(tmp2)
[,1]
[1,] -2.975244
[2,] 2.735577
>
> 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] 6.4215219 -0.5660499 -2.0951836 6.0940180 4.0196967 1.0290604
[7] 4.3190710 -3.1071717 1.4886043 -1.1336871
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.07632857
[2,] 0.31104423
[3,] 0.55096164
[4,] 0.86775985
[5,] 1.67218260
>
> rowApply(tmp,sum)
[1] -2.0151593 -0.1016491 2.9176603 1.0463267 2.2304296 1.3945128
[7] 3.4278138 0.0935492 2.3334265 5.1429693
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 10 8 10 6 7 9 9 6 6 5
[2,] 1 2 8 4 5 3 6 10 9 2
[3,] 9 3 5 2 9 5 2 1 2 1
[4,] 5 4 3 7 10 8 5 4 10 8
[5,] 4 7 6 9 8 6 7 5 8 3
[6,] 3 1 9 3 4 7 10 9 4 4
[7,] 8 9 7 10 2 4 8 2 7 9
[8,] 6 10 2 8 3 1 1 3 1 6
[9,] 7 6 4 5 1 10 4 8 5 7
[10,] 2 5 1 1 6 2 3 7 3 10
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -1.97293693 -0.47727649 -1.07544033 3.85504755 -3.98950132 0.58412468
[7] 4.36400637 -0.03310739 2.81310018 0.61619970 -0.28710042 -1.84799224
[13] 0.66218092 -0.14870572 1.79415201 0.97972461 0.99244104 0.58634525
[19] -0.41581516 -0.24552663
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.9927035
[2,] -0.7786965
[3,] -0.3817191
[4,] -0.1476863
[5,] 0.3278684
>
> rowApply(tmp,sum)
[1] -2.737749 10.039563 -1.804676 -1.754390 3.011171
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 10 9 9 1 4
[2,] 20 6 3 19 1
[3,] 12 2 4 5 17
[4,] 9 19 18 7 19
[5,] 1 4 2 2 16
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -0.1476863 1.0922540 0.1853464 -0.2434026 -2.2494210 0.2758688
[2,] 0.3278684 0.1179886 -0.9631959 1.7089362 -0.3261739 0.9715427
[3,] -0.3817191 -1.4454303 -1.0420363 0.8347395 -1.5082777 0.5416071
[4,] -0.9927035 1.1289524 -0.2968499 -0.2306380 -0.8352992 -0.1491986
[5,] -0.7786965 -1.3710411 1.0412954 1.7854125 0.9296705 -1.0556954
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.83841876 -0.09171255 0.8292494 0.21031810 -1.2274417 -1.0955610
[2,] 2.68411648 0.26058249 1.0075037 0.61200432 -0.9198856 -1.2900819
[3,] 0.58348675 1.13739582 0.7932838 0.41075388 0.8306242 -0.0812122
[4,] -0.05476802 -0.22880801 -0.1617838 -0.64177476 -0.1308486 0.2412311
[5,] 0.31275240 -1.11056514 0.3448471 0.02489816 1.1604513 0.3776318
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 0.3280142 -0.58747507 -0.62029054 -0.32331667 0.73012023 0.9972240
[2,] 0.5334723 0.30674612 0.81898946 -0.05496417 1.17908830 1.5610934
[3,] -0.2988662 -0.97451369 -0.11623708 2.47455031 -0.98359499 -1.6196670
[4,] 0.5387664 1.17427687 -0.08014647 -0.56489499 -0.06123863 -0.1192282
[5,] -0.4392057 -0.06773996 1.79183664 -0.55164987 0.12806613 -0.2330770
[,19] [,20]
[1,] -1.3023564 -0.335898697
[2,] 0.9420337 0.561898296
[3,] -0.5115209 -0.448041664
[4,] -0.2560192 -0.033416716
[5,] 0.7120476 0.009932146
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 654 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 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 0.3325849 -0.2842359 0.3160461 -0.5739036 -0.3822972 0.935957 1.254708
col8 col9 col10 col11 col12 col13 col14
row1 0.3210867 0.8207064 0.06227285 0.2721111 -0.08281743 0.2706837 -0.3611639
col15 col16 col17 col18 col19 col20
row1 1.6748 -0.2924708 -1.073488 0.3710029 0.4181528 -0.1992174
> tmp[,"col10"]
col10
row1 0.06227285
row2 -0.65038980
row3 1.00203014
row4 -0.48092665
row5 1.49832634
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 0.3325849 -0.2842359 0.3160461 -0.5739036 -0.3822972 0.9359570 1.2547083
row5 -0.6145867 0.6529094 0.7151734 1.8050495 0.6299923 0.3235279 -0.4706313
col8 col9 col10 col11 col12 col13
row1 0.3210867 0.8207064 0.06227285 0.27211108 -0.08281743 0.2706837
row5 0.4300846 1.2613597 1.49832634 -0.09815272 0.02933981 0.7931076
col14 col15 col16 col17 col18 col19
row1 -0.3611639 1.6748005 -0.2924708 -1.0734881 0.3710029 0.4181528
row5 -0.4681429 -0.1217198 -0.4052599 0.3563918 -0.1017191 0.5950378
col20
row1 -0.1992174
row5 1.7151328
> tmp[,c("col6","col20")]
col6 col20
row1 0.9359570 -0.1992174
row2 0.8623654 0.3290440
row3 -1.2770921 -0.3302054
row4 -1.2122081 -1.8058867
row5 0.3235279 1.7151328
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 0.9359570 -0.1992174
row5 0.3235279 1.7151328
>
>
>
>
> 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 49.52114 49.39644 49.15843 50.65761 50.32058 104.5439 49.1929 50.08072
col9 col10 col11 col12 col13 col14 col15 col16
row1 51.39615 50.29222 49.84846 51.10309 49.44564 49.57397 48.93069 50.11581
col17 col18 col19 col20
row1 49.12062 49.36838 50.18105 103.6609
> tmp[,"col10"]
col10
row1 50.29222
row2 29.89071
row3 29.78253
row4 30.41803
row5 49.32565
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 49.52114 49.39644 49.15843 50.65761 50.32058 104.5439 49.19290 50.08072
row5 49.94970 49.70330 50.94840 50.88784 50.50040 102.2303 50.64402 48.62044
col9 col10 col11 col12 col13 col14 col15 col16
row1 51.39615 50.29222 49.84846 51.10309 49.44564 49.57397 48.93069 50.11581
row5 50.44552 49.32565 49.59379 49.54869 48.88437 50.23243 50.02134 50.63632
col17 col18 col19 col20
row1 49.12062 49.36838 50.18105 103.6609
row5 49.27785 49.78955 50.42796 105.0516
> tmp[,c("col6","col20")]
col6 col20
row1 104.54386 103.66085
row2 74.61425 75.39309
row3 74.34123 74.83494
row4 74.85261 74.71839
row5 102.23030 105.05162
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 104.5439 103.6609
row5 102.2303 105.0516
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 104.5439 103.6609
row5 102.2303 105.0516
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -0.6268913
[2,] -0.2437221
[3,] -0.5569706
[4,] 1.3591534
[5,] -0.2436493
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.5071052 -1.7614064
[2,] -1.2361521 0.1529746
[3,] -0.7108869 1.0205634
[4,] -1.0030210 -0.7818975
[5,] 1.5622672 -1.1925079
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 0.19609303 0.81621029
[2,] -0.38640314 3.42284252
[3,] -2.07839740 0.64735977
[4,] 0.02326101 1.69912327
[5,] -1.47432883 0.07798692
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 0.196093
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 0.1960930
[2,] -0.3864031
>
>
>
> 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 1.339547 -0.7659295 0.4970925 -0.60442961 0.6518789 0.6046569 -0.9201471
row1 1.290080 -0.4420027 -0.1942955 -0.06951758 0.5745636 0.2383278 -0.3340498
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row3 1.588237 0.2476225 1.431114 -1.3010433 0.6355337 -1.365278 -0.8662498
row1 1.081355 -1.5474837 -0.493309 0.9988244 -2.0294372 0.674803 2.0603635
[,15] [,16] [,17] [,18] [,19] [,20]
row3 1.2591615 -0.7768507 0.8329201 0.1313285 1.685808 0.192894
row1 0.3479592 0.5746338 0.5442252 0.3395459 1.066896 1.037844
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 1.039134 0.5248676 -1.272618 0.5083873 1.303909 0.7779347 0.607802
[,8] [,9] [,10]
row2 0.9524846 0.1260918 -1.096899
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.1425469 -2.575414 -0.2477671 0.009542958 1.951757 1.582184 -1.681715
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.6924007 -2.628185 -1.449376 1.579314 -1.605928 -0.009806254 -0.8397169
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.4748132 -0.7825646 -1.883657 -0.4004938 -0.07708344 0.3677472
>
>
> 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: 0x3acdcca0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM296df6515ddb47"
[2] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM296df6375a615a"
[3] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM296df66dfb9f5d"
[4] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM296df67f490c5a"
[5] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM296df64f8620dd"
[6] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM296df6453503d7"
[7] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM296df660f77b44"
[8] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM296df6155ddef7"
[9] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM296df64bd2e99f"
[10] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM296df62be27327"
[11] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM296df66d5661ae"
[12] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM296df614062d49"
[13] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM296df6125ceaa4"
[14] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM296df63c858f57"
[15] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM296df644b32bd1"
>
>
> ### 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: 0x38ba5d40>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x38ba5d40>
Warning message:
In dir.create(new.directory) :
'/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x38ba5d40>
> rowMedians(tmp)
[1] -0.250484711 0.057414698 0.262179336 0.055044335 0.201247829
[6] -0.320676241 -0.056475005 -0.364445053 -0.205649067 0.497631284
[11] 0.262451085 0.048274532 -0.254632638 0.218191989 0.422480132
[16] 0.059889567 0.576462876 -0.315144994 -0.357128170 -0.555449822
[21] 0.357880951 0.075314673 0.308482210 0.240810419 -0.276017950
[26] 0.143474928 -0.605411221 0.268397332 -0.460805278 -0.555147786
[31] -0.475229896 -0.732490079 -0.042894370 0.059415045 -0.075419508
[36] -0.153671700 0.226357799 -0.154765707 0.066400346 0.143478564
[41] -0.109747932 0.191671413 -0.634628264 -0.299443974 0.267072232
[46] -0.184467476 0.199866627 0.331326900 0.196398145 0.098970580
[51] 0.058395907 0.551950836 0.155851630 -0.216571505 -0.556200574
[56] -0.155452607 0.469228364 0.256794477 -0.077298982 -0.292109816
[61] -0.008874688 -0.079043731 -0.226816497 0.040883695 -0.071210108
[66] -0.173318334 -0.052946570 0.247534492 -0.352100481 0.127793768
[71] -0.073127984 0.180846195 -0.600312286 -0.507249658 0.251669291
[76] -0.492312123 -0.157736348 -0.182066790 -0.123863127 -0.270200169
[81] -0.088343348 0.246626738 0.042662882 -0.620209708 0.173608901
[86] -0.167744713 -0.535505227 -0.346206888 0.472919038 -0.018384346
[91] 0.394077575 0.015951912 -0.274312240 -0.098223666 -0.035750270
[96] -0.036733131 0.187506945 0.621575359 0.168211636 0.316163333
[101] 0.137446199 0.028169337 0.217020357 -0.365414664 0.348740053
[106] -0.318249274 -0.408830748 0.290310524 -0.545199540 -0.168275018
[111] -0.108237584 -0.050457944 0.056121429 0.179460025 0.151113677
[116] 0.641639867 0.138660094 0.292004025 0.115850049 0.013888781
[121] -0.136845352 -0.075088731 -0.112270034 0.468079008 0.189350867
[126] 0.261661527 -0.204108918 -0.074725985 -0.250597977 -0.157674097
[131] 0.375748096 0.030683953 -0.249035699 0.080889042 -0.295631469
[136] -0.580850212 0.090603366 0.163407700 0.574777871 -0.029756562
[141] -0.323664064 0.384428489 -0.084722972 0.300144039 -0.146762980
[146] 0.286828302 -0.258488009 -0.733277452 0.073901030 0.145607875
[151] -0.191579794 -0.484321198 0.312408707 -0.168962542 0.072355840
[156] 0.325892908 -0.210783296 0.148298609 0.145839432 -0.235540991
[161] 0.149394249 -0.192259821 0.314285494 -0.166467252 0.192343595
[166] -0.065446131 0.433052592 -1.019076152 -0.286340776 0.553942715
[171] -0.362711318 0.531751338 0.176088523 -0.182674989 0.524147440
[176] 0.088707104 -0.139504022 -0.134358870 -0.611458963 0.763441607
[181] 0.437402308 0.002840262 0.007759940 0.123926664 0.184767679
[186] 0.008444416 -0.225750271 0.315097600 0.108821350 0.072432235
[191] -0.009454209 -0.043882907 -0.557826016 -0.476897076 0.033316143
[196] 0.103332661 -0.420011425 -0.269352112 0.660878351 -0.159475262
[201] -0.166057059 -0.228366545 0.157553649 0.120171490 0.048995463
[206] -0.196739463 -0.111802124 -0.244695568 0.517171526 -0.014830605
[211] 0.080506480 0.522375158 -0.990037983 0.139978708 -0.144154004
[216] 0.528435749 0.221456843 0.598653664 -0.150098712 -0.193711164
[221] -0.133241017 0.136644121 -0.023767503 -0.100249963 0.476854929
[226] 0.186863502 -0.178753307 0.248772076 -0.059436360 0.184961504
>
> proc.time()
user system elapsed
1.900 0.810 2.736
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: 0x2b480ff0>
> .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: 0x2b480ff0>
> .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: 0x2b480ff0>
> .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: 0x2b480ff0>
> 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: 0x2b38b470>
> .Call("R_bm_AddColumn",P)
<pointer: 0x2b38b470>
> .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: 0x2b38b470>
> .Call("R_bm_AddColumn",P)
<pointer: 0x2b38b470>
> .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: 0x2b38b470>
> 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: 0x2b3660e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x2b3660e0>
> .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: 0x2b3660e0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x2b3660e0>
> .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: 0x2b3660e0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x2b3660e0>
> .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: 0x2b3660e0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x2b3660e0>
> .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: 0x2b3660e0>
> 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: 0x2a2ed520>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x2a2ed520>
> .Call("R_bm_AddColumn",P)
<pointer: 0x2a2ed520>
> .Call("R_bm_AddColumn",P)
<pointer: 0x2a2ed520>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile296e2920db255" "BufferedMatrixFile296e2958e2f608"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile296e2920db255" "BufferedMatrixFile296e2958e2f608"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x2c236030>
> .Call("R_bm_AddColumn",P)
<pointer: 0x2c236030>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x2c236030>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x2c236030>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x2c236030>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x2c236030>
> .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: 0x2ac015c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x2ac015c0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x2ac015c0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x2ac015c0>
> 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: 0x2bce1f30>
> .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: 0x2bce1f30>
> rm(P)
>
> proc.time()
user system elapsed
0.347 0.045 0.377
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
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You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
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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
0.330 0.032 0.350