Ben Bolstad
| Snapshot Date: 2025-08-14 13:45 -0400 (Thu, 14 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 2025-08-15 12:06 -0400 (Fri, 15 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" | 4818 |
| palomino8 | Windows Server 2022 Datacenter | x64 | 4.5.1 (2025-06-13 ucrt) -- "Great Square Root" | 4554 |
| lconway | macOS 12.7.1 Monterey | x86_64 | 4.5.1 (2025-06-13) -- "Great Square Root" | 4595 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | 4.5.1 Patched (2025-06-14 r88325) -- "Great Square Root" | 4537 |
| taishan | Linux (openEuler 24.03 LTS) | aarch64 | 4.5.0 (2025-04-11) -- "How About a Twenty-Six" | 4535 |
| 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 251/2317 | 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 | | ||||||||
| palomino8 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | | ||||||||
| lconway | macOS 12.7.1 Monterey / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| kjohnson3 | macOS 13.7.7 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. |
| Package: BufferedMatrix |
| Version: 1.73.0 |
| Command: F:\biocbuild\bbs-3.22-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:BufferedMatrix.install-out.txt --library=F:\biocbuild\bbs-3.22-bioc\R\library --no-vignettes --timings BufferedMatrix_1.73.0.tar.gz |
| StartedAt: 2025-08-15 01:14:37 -0400 (Fri, 15 Aug 2025) |
| EndedAt: 2025-08-15 01:17:19 -0400 (Fri, 15 Aug 2025) |
| EllapsedTime: 162.2 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### F:\biocbuild\bbs-3.22-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:BufferedMatrix.install-out.txt --library=F:\biocbuild\bbs-3.22-bioc\R\library --no-vignettes --timings BufferedMatrix_1.73.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory 'F:/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck'
* using R version 4.5.1 (2025-06-13 ucrt)
* using platform: x86_64-w64-mingw32
* R was compiled by
gcc.exe (GCC) 14.2.0
GNU Fortran (GCC) 14.2.0
* running under: Windows Server 2022 x64 (build 20348)
* 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 whether package 'BufferedMatrix' can be installed ... OK
* used C compiler: 'gcc.exe (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 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 for x64 is not available
File 'F:/biocbuild/bbs-3.22-bioc/R/library/BufferedMatrix/libs/x64/BufferedMatrix.dll':
Found '_exit', possibly from '_exit' (C)
Found 'abort', possibly from 'abort' (C), 'runtime' (Fortran)
Compiled code should not call entry points which might terminate R nor
write to stdout/stderr instead of to the console, nor use Fortran I/O
nor system RNGs nor [v]sprintf. The detected symbols are linked into
the code but might come from libraries and not actually be called.
See 'Writing portable packages' in the 'Writing R Extensions' manual.
* checking sizes of PDF files under 'inst/doc' ... OK
* checking files in 'vignettes' ... OK
* checking examples ... NONE
* checking for unstated dependencies in 'tests' ... OK
* checking tests ...
Running 'Rcodetesting.R'
Running 'c_code_level_tests.R'
Running 'objectTesting.R'
Running 'rawCalltesting.R'
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE
Status: 2 NOTEs
See
'F:/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/00check.log'
for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### F:\biocbuild\bbs-3.22-bioc\R\bin\R.exe CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library 'F:/biocbuild/bbs-3.22-bioc/R/library'
* installing *source* package 'BufferedMatrix' ...
** this is package 'BufferedMatrix' version '1.73.0'
** using staged installation
** libs
using C compiler: 'gcc.exe (GCC) 14.2.0'
gcc -I"F:/biocbuild/bbs-3.22-bioc/R/include" -DNDEBUG -I"C:/rtools45/x86_64-w64-mingw32.static.posix/include" -O2 -Wall -std=gnu2x -mfpmath=sse -msse2 -mstackrealign -c RBufferedMatrix.c -o RBufferedMatrix.o
gcc -I"F:/biocbuild/bbs-3.22-bioc/R/include" -DNDEBUG -I"C:/rtools45/x86_64-w64-mingw32.static.posix/include" -O2 -Wall -std=gnu2x -mfpmath=sse -msse2 -mstackrealign -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){
| ^~~~~~~~~~~
gcc -I"F:/biocbuild/bbs-3.22-bioc/R/include" -DNDEBUG -I"C:/rtools45/x86_64-w64-mingw32.static.posix/include" -O2 -Wall -std=gnu2x -mfpmath=sse -msse2 -mstackrealign -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
gcc -I"F:/biocbuild/bbs-3.22-bioc/R/include" -DNDEBUG -I"C:/rtools45/x86_64-w64-mingw32.static.posix/include" -O2 -Wall -std=gnu2x -mfpmath=sse -msse2 -mstackrealign -c init_package.c -o init_package.o
gcc -shared -s -static-libgcc -o BufferedMatrix.dll tmp.def RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -LC:/rtools45/x86_64-w64-mingw32.static.posix/lib/x64 -LC:/rtools45/x86_64-w64-mingw32.static.posix/lib -LF:/biocbuild/bbs-3.22-bioc/R/bin/x64 -lR
installing to F:/biocbuild/bbs-3.22-bioc/R/library/00LOCK-BufferedMatrix/00new/BufferedMatrix/libs/x64
** 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
** 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 4.5.1 (2025-06-13 ucrt) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64
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
0.43 0.17 1.28
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.5.1 (2025-06-13 ucrt) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64
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] "F:/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 475147 25.4 1042854 55.7 629417 33.7
Vcells 867347 6.7 8388608 64.0 2039165 15.6
>
>
>
>
> ##
> ## 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 15 01:15:16 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 15 01:15:18 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: 0x000001eb3b2f8a70>
>
>
>
> 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 15 01:15:40 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 15 01:15:47 2025"
>
> ColMode(tmp2)
<pointer: 0x000001eb3b2f8a70>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 101.2084969 -2.8295150 0.0695989 -2.0068861
[2,] -0.1281473 0.0409521 1.4671359 0.2575151
[3,] -0.2640608 -0.2657612 2.1680831 -1.0356287
[4,] 0.4232301 0.7703574 1.1485015 1.1578187
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: F:/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,] 101.2084969 2.8295150 0.0695989 2.0068861
[2,] 0.1281473 0.0409521 1.4671359 0.2575151
[3,] 0.2640608 0.2657612 2.1680831 1.0356287
[4,] 0.4232301 0.7703574 1.1485015 1.1578187
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: F:/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,] 10.0602434 1.6821162 0.263816 1.4166461
[2,] 0.3579767 0.2023663 1.211254 0.5074594
[3,] 0.5138685 0.5155204 1.472441 1.0176584
[4,] 0.6505613 0.8777001 1.071682 1.0760199
>
> 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: F:/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,] 226.81093 44.65068 27.70776 41.17335
[2,] 28.70791 27.06461 38.57967 30.33211
[3,] 30.40275 30.42096 41.89250 36.21221
[4,] 31.92884 34.54736 36.86532 36.91802
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x000001eb3b2f8290>
> exp(tmp5)
<pointer: 0x000001eb3b2f8290>
> log(tmp5,2)
<pointer: 0x000001eb3b2f8290>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 472.0772
> Min(tmp5)
[1] 55.2757
> mean(tmp5)
[1] 74.07595
> Sum(tmp5)
[1] 14815.19
> Var(tmp5)
[1] 878.6829
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 93.49959 69.20147 73.54014 72.08975 72.08013 72.94287 73.06162 69.87056
[9] 70.52523 73.94816
> rowSums(tmp5)
[1] 1869.992 1384.029 1470.803 1441.795 1441.603 1458.857 1461.232 1397.411
[9] 1410.505 1478.963
> rowVars(tmp5)
[1] 8073.22012 70.89505 116.76687 49.40362 95.92762 87.02975
[7] 53.44243 67.00647 71.21708 53.00601
> rowSd(tmp5)
[1] 89.851100 8.419920 10.805872 7.028771 9.794265 9.328973 7.310433
[8] 8.185748 8.439021 7.280523
> rowMax(tmp5)
[1] 472.07724 83.35497 100.04144 87.52278 90.79738 87.23663 84.10689
[8] 84.68685 92.68045 83.46900
> rowMin(tmp5)
[1] 55.64086 56.07867 59.61914 59.67871 57.04315 56.00141 57.08003 56.06382
[9] 55.27570 56.08790
>
> colMeans(tmp5)
[1] 110.30664 72.00624 75.18580 75.77188 69.44071 72.87305 69.99511
[8] 69.36899 71.54788 71.82453 75.36258 76.55295 70.24243 70.62628
[15] 69.89921 73.35396 74.53722 65.89092 71.49945 75.23322
> colSums(tmp5)
[1] 1103.0664 720.0624 751.8580 757.7188 694.4071 728.7305 699.9511
[8] 693.6899 715.4788 718.2453 753.6258 765.5295 702.4243 706.2628
[15] 698.9921 733.5396 745.3722 658.9092 714.9945 752.3322
> colVars(tmp5)
[1] 16223.37360 111.63347 100.25319 82.70237 49.91203 67.21356
[7] 60.30549 74.75928 41.14174 47.12045 10.73595 192.99766
[13] 122.10665 61.51554 88.58243 96.76226 62.39412 63.91636
[19] 126.24533 54.10126
> colSd(tmp5)
[1] 127.371008 10.565674 10.012651 9.094085 7.064845 8.198387
[7] 7.765661 8.646345 6.414183 6.864434 3.276575 13.892360
[13] 11.050188 7.843184 9.411824 9.836781 7.898995 7.994771
[19] 11.235895 7.355356
> colMax(tmp5)
[1] 472.07724 92.93453 87.32359 90.79738 85.80575 87.23663 80.92949
[8] 82.42558 78.18672 80.76325 79.58867 100.04144 84.62942 83.18046
[15] 83.35497 87.52278 88.93056 78.59726 87.94068 90.27274
> colMin(tmp5)
[1] 59.75176 56.33145 57.67007 60.82230 59.72239 59.58879 59.00824 55.98844
[9] 59.50347 62.78696 68.40052 59.67871 57.04315 56.07867 55.64086 56.06382
[17] 64.23197 55.27570 56.08790 66.20964
>
>
> ### 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] 93.49959 69.20147 73.54014 72.08975 72.08013 72.94287 73.06162 69.87056
[9] 70.52523 NA
> rowSums(tmp5)
[1] 1869.992 1384.029 1470.803 1441.795 1441.603 1458.857 1461.232 1397.411
[9] 1410.505 NA
> rowVars(tmp5)
[1] 8073.22012 70.89505 116.76687 49.40362 95.92762 87.02975
[7] 53.44243 67.00647 71.21708 55.88510
> rowSd(tmp5)
[1] 89.851100 8.419920 10.805872 7.028771 9.794265 9.328973 7.310433
[8] 8.185748 8.439021 7.475634
> rowMax(tmp5)
[1] 472.07724 83.35497 100.04144 87.52278 90.79738 87.23663 84.10689
[8] 84.68685 92.68045 NA
> rowMin(tmp5)
[1] 55.64086 56.07867 59.61914 59.67871 57.04315 56.00141 57.08003 56.06382
[9] 55.27570 NA
>
> colMeans(tmp5)
[1] 110.30664 72.00624 75.18580 75.77188 69.44071 72.87305 69.99511
[8] 69.36899 71.54788 71.82453 75.36258 76.55295 70.24243 70.62628
[15] 69.89921 73.35396 74.53722 65.89092 71.49945 NA
> colSums(tmp5)
[1] 1103.0664 720.0624 751.8580 757.7188 694.4071 728.7305 699.9511
[8] 693.6899 715.4788 718.2453 753.6258 765.5295 702.4243 706.2628
[15] 698.9921 733.5396 745.3722 658.9092 714.9945 NA
> colVars(tmp5)
[1] 16223.37360 111.63347 100.25319 82.70237 49.91203 67.21356
[7] 60.30549 74.75928 41.14174 47.12045 10.73595 192.99766
[13] 122.10665 61.51554 88.58243 96.76226 62.39412 63.91636
[19] 126.24533 NA
> colSd(tmp5)
[1] 127.371008 10.565674 10.012651 9.094085 7.064845 8.198387
[7] 7.765661 8.646345 6.414183 6.864434 3.276575 13.892360
[13] 11.050188 7.843184 9.411824 9.836781 7.898995 7.994771
[19] 11.235895 NA
> colMax(tmp5)
[1] 472.07724 92.93453 87.32359 90.79738 85.80575 87.23663 80.92949
[8] 82.42558 78.18672 80.76325 79.58867 100.04144 84.62942 83.18046
[15] 83.35497 87.52278 88.93056 78.59726 87.94068 NA
> colMin(tmp5)
[1] 59.75176 56.33145 57.67007 60.82230 59.72239 59.58879 59.00824 55.98844
[9] 59.50347 62.78696 68.40052 59.67871 57.04315 56.07867 55.64086 56.06382
[17] 64.23197 55.27570 56.08790 NA
>
> Max(tmp5,na.rm=TRUE)
[1] 472.0772
> Min(tmp5,na.rm=TRUE)
[1] 55.2757
> mean(tmp5,na.rm=TRUE)
[1] 74.08192
> Sum(tmp5,na.rm=TRUE)
[1] 14742.3
> Var(tmp5,na.rm=TRUE)
[1] 883.1135
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 93.49959 69.20147 73.54014 72.08975 72.08013 72.94287 73.06162 69.87056
[9] 70.52523 74.00394
> rowSums(tmp5,na.rm=TRUE)
[1] 1869.992 1384.029 1470.803 1441.795 1441.603 1458.857 1461.232 1397.411
[9] 1410.505 1406.075
> rowVars(tmp5,na.rm=TRUE)
[1] 8073.22012 70.89505 116.76687 49.40362 95.92762 87.02975
[7] 53.44243 67.00647 71.21708 55.88510
> rowSd(tmp5,na.rm=TRUE)
[1] 89.851100 8.419920 10.805872 7.028771 9.794265 9.328973 7.310433
[8] 8.185748 8.439021 7.475634
> rowMax(tmp5,na.rm=TRUE)
[1] 472.07724 83.35497 100.04144 87.52278 90.79738 87.23663 84.10689
[8] 84.68685 92.68045 83.46900
> rowMin(tmp5,na.rm=TRUE)
[1] 55.64086 56.07867 59.61914 59.67871 57.04315 56.00141 57.08003 56.06382
[9] 55.27570 56.08790
>
> colMeans(tmp5,na.rm=TRUE)
[1] 110.30664 72.00624 75.18580 75.77188 69.44071 72.87305 69.99511
[8] 69.36899 71.54788 71.82453 75.36258 76.55295 70.24243 70.62628
[15] 69.89921 73.35396 74.53722 65.89092 71.49945 75.49377
> colSums(tmp5,na.rm=TRUE)
[1] 1103.0664 720.0624 751.8580 757.7188 694.4071 728.7305 699.9511
[8] 693.6899 715.4788 718.2453 753.6258 765.5295 702.4243 706.2628
[15] 698.9921 733.5396 745.3722 658.9092 714.9945 679.4439
> colVars(tmp5,na.rm=TRUE)
[1] 16223.37360 111.63347 100.25319 82.70237 49.91203 67.21356
[7] 60.30549 74.75928 41.14174 47.12045 10.73595 192.99766
[13] 122.10665 61.51554 88.58243 96.76226 62.39412 63.91636
[19] 126.24533 60.10019
> colSd(tmp5,na.rm=TRUE)
[1] 127.371008 10.565674 10.012651 9.094085 7.064845 8.198387
[7] 7.765661 8.646345 6.414183 6.864434 3.276575 13.892360
[13] 11.050188 7.843184 9.411824 9.836781 7.898995 7.994771
[19] 11.235895 7.752431
> colMax(tmp5,na.rm=TRUE)
[1] 472.07724 92.93453 87.32359 90.79738 85.80575 87.23663 80.92949
[8] 82.42558 78.18672 80.76325 79.58867 100.04144 84.62942 83.18046
[15] 83.35497 87.52278 88.93056 78.59726 87.94068 90.27274
> colMin(tmp5,na.rm=TRUE)
[1] 59.75176 56.33145 57.67007 60.82230 59.72239 59.58879 59.00824 55.98844
[9] 59.50347 62.78696 68.40052 59.67871 57.04315 56.07867 55.64086 56.06382
[17] 64.23197 55.27570 56.08790 66.20964
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 93.49959 69.20147 73.54014 72.08975 72.08013 72.94287 73.06162 69.87056
[9] 70.52523 NaN
> rowSums(tmp5,na.rm=TRUE)
[1] 1869.992 1384.029 1470.803 1441.795 1441.603 1458.857 1461.232 1397.411
[9] 1410.505 0.000
> rowVars(tmp5,na.rm=TRUE)
[1] 8073.22012 70.89505 116.76687 49.40362 95.92762 87.02975
[7] 53.44243 67.00647 71.21708 NA
> rowSd(tmp5,na.rm=TRUE)
[1] 89.851100 8.419920 10.805872 7.028771 9.794265 9.328973 7.310433
[8] 8.185748 8.439021 NA
> rowMax(tmp5,na.rm=TRUE)
[1] 472.07724 83.35497 100.04144 87.52278 90.79738 87.23663 84.10689
[8] 84.68685 92.68045 NA
> rowMin(tmp5,na.rm=TRUE)
[1] 55.64086 56.07867 59.61914 59.67871 57.04315 56.00141 57.08003 56.06382
[9] 55.27570 NA
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 113.71865 72.78492 75.39553 75.45148 69.47506 71.97194 70.91446
[8] 68.42510 70.84071 71.44170 75.35234 78.00214 68.97941 70.06299
[15] 69.07714 73.17996 73.54480 64.47910 73.21185 NaN
> colSums(tmp5,na.rm=TRUE)
[1] 1023.4679 655.0643 678.5598 679.0634 625.2755 647.7474 638.2302
[8] 615.8259 637.5664 642.9753 678.1710 702.0193 620.8147 630.5669
[15] 621.6943 658.6197 661.9032 580.3119 658.9066 0.0000
> colVars(tmp5,na.rm=TRUE)
[1] 18120.32490 118.76628 112.29001 91.88529 56.13777 66.48019
[7] 58.33504 74.08108 40.65837 51.36169 12.07676 193.49540
[13] 119.42382 65.63547 92.05255 108.51695 59.11329 49.48215
[19] 109.03766 NA
> colSd(tmp5,na.rm=TRUE)
[1] 134.611756 10.897994 10.596698 9.585682 7.492514 8.153538
[7] 7.637738 8.607036 6.376392 7.166707 3.475163 13.910262
[13] 10.928121 8.101572 9.594402 10.417147 7.688516 7.034355
[19] 10.442110 NA
> colMax(tmp5,na.rm=TRUE)
[1] 472.07724 92.93453 87.32359 90.79738 85.80575 87.23663 80.92949
[8] 82.42558 78.18672 80.76325 79.58867 100.04144 84.62942 83.18046
[15] 83.35497 87.52278 88.93056 75.13037 87.94068 -Inf
> colMin(tmp5,na.rm=TRUE)
[1] 59.75176 56.33145 57.67007 60.82230 59.72239 59.58879 59.00824 55.98844
[9] 59.50347 62.78696 68.40052 59.67871 57.04315 56.07867 55.64086 56.06382
[17] 64.23197 55.27570 59.81141 Inf
>
>
>
>
> 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] 114.1871 215.4950 376.7540 243.2090 206.3900 229.6723 210.1836 146.5605
[9] 178.0152 217.1054
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 114.1871 215.4950 376.7540 243.2090 206.3900 229.6723 210.1836 146.5605
[9] 178.0152 217.1054
>
>
>
> 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 -2.842171e-14 1.563194e-13 2.842171e-14 2.415845e-13
[6] -5.684342e-14 0.000000e+00 1.989520e-13 -5.684342e-14 5.684342e-14
[11] 1.421085e-14 -8.526513e-14 0.000000e+00 -8.526513e-14 3.979039e-13
[16] 0.000000e+00 1.136868e-13 0.000000e+00 5.684342e-14 -1.421085e-13
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
7 4
3 13
4 4
6 10
5 10
2 5
2 15
3 1
9 6
6 11
8 3
4 9
7 18
5 2
9 8
1 9
2 14
5 5
9 9
4 2
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] 3.095899
> Min(tmp)
[1] -2.607726
> mean(tmp)
[1] -0.05112455
> Sum(tmp)
[1] -5.112455
> Var(tmp)
[1] 1.239429
>
> rowMeans(tmp)
[1] -0.05112455
> rowSums(tmp)
[1] -5.112455
> rowVars(tmp)
[1] 1.239429
> rowSd(tmp)
[1] 1.113297
> rowMax(tmp)
[1] 3.095899
> rowMin(tmp)
[1] -2.607726
>
> colMeans(tmp)
[1] 0.651524322 0.478480147 1.623810293 -1.328275781 0.512120976
[6] 2.091895483 1.842642479 0.480709374 1.582473832 0.623127191
[11] -1.444567874 1.919313109 -0.469331423 0.159172798 -0.154780459
[16] 1.170627976 -0.192495445 -1.762148278 0.047523342 -0.226451306
[21] -0.447006406 -1.041567393 -0.169101340 1.847246796 0.063943539
[26] 0.332824183 -1.387689064 -0.938303675 -0.992083534 -2.607725571
[31] -2.033770118 -0.347677724 2.348790957 -1.771243718 -0.638682991
[36] -0.621709516 0.668728353 -0.072458377 -1.461278713 0.454728792
[41] 0.595811045 0.038593034 -0.320993645 -0.506098842 -0.307987798
[46] -0.691896069 -0.399579674 0.683425421 -0.008132656 0.238433304
[51] 0.428007196 -0.914425765 -0.582268775 0.725958426 0.456417300
[56] 0.050313615 0.436215199 -2.139706488 0.582104954 0.297316998
[61] -1.694754601 -0.326858822 -0.371090469 -1.156016126 0.884820396
[66] 0.646799408 -1.719350907 0.162138506 -2.484634113 0.428767199
[71] 3.095898502 0.155714640 -1.111851523 1.033433204 -0.035024128
[76] -1.453940310 -0.940192805 -0.084828882 0.463177113 1.962436074
[81] 2.753315889 -0.172932258 -1.122689994 0.374532299 -1.002045329
[86] -0.632512878 0.071252620 0.191889029 0.651390201 -0.738525837
[91] 1.541850780 -1.319425087 0.207112250 1.215167440 -1.438027144
[96] 0.113366626 -0.293842664 0.809946686 -1.019461200 -0.210300619
> colSums(tmp)
[1] 0.651524322 0.478480147 1.623810293 -1.328275781 0.512120976
[6] 2.091895483 1.842642479 0.480709374 1.582473832 0.623127191
[11] -1.444567874 1.919313109 -0.469331423 0.159172798 -0.154780459
[16] 1.170627976 -0.192495445 -1.762148278 0.047523342 -0.226451306
[21] -0.447006406 -1.041567393 -0.169101340 1.847246796 0.063943539
[26] 0.332824183 -1.387689064 -0.938303675 -0.992083534 -2.607725571
[31] -2.033770118 -0.347677724 2.348790957 -1.771243718 -0.638682991
[36] -0.621709516 0.668728353 -0.072458377 -1.461278713 0.454728792
[41] 0.595811045 0.038593034 -0.320993645 -0.506098842 -0.307987798
[46] -0.691896069 -0.399579674 0.683425421 -0.008132656 0.238433304
[51] 0.428007196 -0.914425765 -0.582268775 0.725958426 0.456417300
[56] 0.050313615 0.436215199 -2.139706488 0.582104954 0.297316998
[61] -1.694754601 -0.326858822 -0.371090469 -1.156016126 0.884820396
[66] 0.646799408 -1.719350907 0.162138506 -2.484634113 0.428767199
[71] 3.095898502 0.155714640 -1.111851523 1.033433204 -0.035024128
[76] -1.453940310 -0.940192805 -0.084828882 0.463177113 1.962436074
[81] 2.753315889 -0.172932258 -1.122689994 0.374532299 -1.002045329
[86] -0.632512878 0.071252620 0.191889029 0.651390201 -0.738525837
[91] 1.541850780 -1.319425087 0.207112250 1.215167440 -1.438027144
[96] 0.113366626 -0.293842664 0.809946686 -1.019461200 -0.210300619
> 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] 0.651524322 0.478480147 1.623810293 -1.328275781 0.512120976
[6] 2.091895483 1.842642479 0.480709374 1.582473832 0.623127191
[11] -1.444567874 1.919313109 -0.469331423 0.159172798 -0.154780459
[16] 1.170627976 -0.192495445 -1.762148278 0.047523342 -0.226451306
[21] -0.447006406 -1.041567393 -0.169101340 1.847246796 0.063943539
[26] 0.332824183 -1.387689064 -0.938303675 -0.992083534 -2.607725571
[31] -2.033770118 -0.347677724 2.348790957 -1.771243718 -0.638682991
[36] -0.621709516 0.668728353 -0.072458377 -1.461278713 0.454728792
[41] 0.595811045 0.038593034 -0.320993645 -0.506098842 -0.307987798
[46] -0.691896069 -0.399579674 0.683425421 -0.008132656 0.238433304
[51] 0.428007196 -0.914425765 -0.582268775 0.725958426 0.456417300
[56] 0.050313615 0.436215199 -2.139706488 0.582104954 0.297316998
[61] -1.694754601 -0.326858822 -0.371090469 -1.156016126 0.884820396
[66] 0.646799408 -1.719350907 0.162138506 -2.484634113 0.428767199
[71] 3.095898502 0.155714640 -1.111851523 1.033433204 -0.035024128
[76] -1.453940310 -0.940192805 -0.084828882 0.463177113 1.962436074
[81] 2.753315889 -0.172932258 -1.122689994 0.374532299 -1.002045329
[86] -0.632512878 0.071252620 0.191889029 0.651390201 -0.738525837
[91] 1.541850780 -1.319425087 0.207112250 1.215167440 -1.438027144
[96] 0.113366626 -0.293842664 0.809946686 -1.019461200 -0.210300619
> colMin(tmp)
[1] 0.651524322 0.478480147 1.623810293 -1.328275781 0.512120976
[6] 2.091895483 1.842642479 0.480709374 1.582473832 0.623127191
[11] -1.444567874 1.919313109 -0.469331423 0.159172798 -0.154780459
[16] 1.170627976 -0.192495445 -1.762148278 0.047523342 -0.226451306
[21] -0.447006406 -1.041567393 -0.169101340 1.847246796 0.063943539
[26] 0.332824183 -1.387689064 -0.938303675 -0.992083534 -2.607725571
[31] -2.033770118 -0.347677724 2.348790957 -1.771243718 -0.638682991
[36] -0.621709516 0.668728353 -0.072458377 -1.461278713 0.454728792
[41] 0.595811045 0.038593034 -0.320993645 -0.506098842 -0.307987798
[46] -0.691896069 -0.399579674 0.683425421 -0.008132656 0.238433304
[51] 0.428007196 -0.914425765 -0.582268775 0.725958426 0.456417300
[56] 0.050313615 0.436215199 -2.139706488 0.582104954 0.297316998
[61] -1.694754601 -0.326858822 -0.371090469 -1.156016126 0.884820396
[66] 0.646799408 -1.719350907 0.162138506 -2.484634113 0.428767199
[71] 3.095898502 0.155714640 -1.111851523 1.033433204 -0.035024128
[76] -1.453940310 -0.940192805 -0.084828882 0.463177113 1.962436074
[81] 2.753315889 -0.172932258 -1.122689994 0.374532299 -1.002045329
[86] -0.632512878 0.071252620 0.191889029 0.651390201 -0.738525837
[91] 1.541850780 -1.319425087 0.207112250 1.215167440 -1.438027144
[96] 0.113366626 -0.293842664 0.809946686 -1.019461200 -0.210300619
> colMedians(tmp)
[1] 0.651524322 0.478480147 1.623810293 -1.328275781 0.512120976
[6] 2.091895483 1.842642479 0.480709374 1.582473832 0.623127191
[11] -1.444567874 1.919313109 -0.469331423 0.159172798 -0.154780459
[16] 1.170627976 -0.192495445 -1.762148278 0.047523342 -0.226451306
[21] -0.447006406 -1.041567393 -0.169101340 1.847246796 0.063943539
[26] 0.332824183 -1.387689064 -0.938303675 -0.992083534 -2.607725571
[31] -2.033770118 -0.347677724 2.348790957 -1.771243718 -0.638682991
[36] -0.621709516 0.668728353 -0.072458377 -1.461278713 0.454728792
[41] 0.595811045 0.038593034 -0.320993645 -0.506098842 -0.307987798
[46] -0.691896069 -0.399579674 0.683425421 -0.008132656 0.238433304
[51] 0.428007196 -0.914425765 -0.582268775 0.725958426 0.456417300
[56] 0.050313615 0.436215199 -2.139706488 0.582104954 0.297316998
[61] -1.694754601 -0.326858822 -0.371090469 -1.156016126 0.884820396
[66] 0.646799408 -1.719350907 0.162138506 -2.484634113 0.428767199
[71] 3.095898502 0.155714640 -1.111851523 1.033433204 -0.035024128
[76] -1.453940310 -0.940192805 -0.084828882 0.463177113 1.962436074
[81] 2.753315889 -0.172932258 -1.122689994 0.374532299 -1.002045329
[86] -0.632512878 0.071252620 0.191889029 0.651390201 -0.738525837
[91] 1.541850780 -1.319425087 0.207112250 1.215167440 -1.438027144
[96] 0.113366626 -0.293842664 0.809946686 -1.019461200 -0.210300619
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8]
[1,] 0.6515243 0.4784801 1.62381 -1.328276 0.512121 2.091895 1.842642 0.4807094
[2,] 0.6515243 0.4784801 1.62381 -1.328276 0.512121 2.091895 1.842642 0.4807094
[,9] [,10] [,11] [,12] [,13] [,14] [,15]
[1,] 1.582474 0.6231272 -1.444568 1.919313 -0.4693314 0.1591728 -0.1547805
[2,] 1.582474 0.6231272 -1.444568 1.919313 -0.4693314 0.1591728 -0.1547805
[,16] [,17] [,18] [,19] [,20] [,21] [,22]
[1,] 1.170628 -0.1924954 -1.762148 0.04752334 -0.2264513 -0.4470064 -1.041567
[2,] 1.170628 -0.1924954 -1.762148 0.04752334 -0.2264513 -0.4470064 -1.041567
[,23] [,24] [,25] [,26] [,27] [,28] [,29]
[1,] -0.1691013 1.847247 0.06394354 0.3328242 -1.387689 -0.9383037 -0.9920835
[2,] -0.1691013 1.847247 0.06394354 0.3328242 -1.387689 -0.9383037 -0.9920835
[,30] [,31] [,32] [,33] [,34] [,35] [,36]
[1,] -2.607726 -2.03377 -0.3476777 2.348791 -1.771244 -0.638683 -0.6217095
[2,] -2.607726 -2.03377 -0.3476777 2.348791 -1.771244 -0.638683 -0.6217095
[,37] [,38] [,39] [,40] [,41] [,42] [,43]
[1,] 0.6687284 -0.07245838 -1.461279 0.4547288 0.595811 0.03859303 -0.3209936
[2,] 0.6687284 -0.07245838 -1.461279 0.4547288 0.595811 0.03859303 -0.3209936
[,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.5060988 -0.3079878 -0.6918961 -0.3995797 0.6834254 -0.008132656
[2,] -0.5060988 -0.3079878 -0.6918961 -0.3995797 0.6834254 -0.008132656
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 0.2384333 0.4280072 -0.9144258 -0.5822688 0.7259584 0.4564173 0.05031361
[2,] 0.2384333 0.4280072 -0.9144258 -0.5822688 0.7259584 0.4564173 0.05031361
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 0.4362152 -2.139706 0.582105 0.297317 -1.694755 -0.3268588 -0.3710905
[2,] 0.4362152 -2.139706 0.582105 0.297317 -1.694755 -0.3268588 -0.3710905
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] -1.156016 0.8848204 0.6467994 -1.719351 0.1621385 -2.484634 0.4287672
[2,] -1.156016 0.8848204 0.6467994 -1.719351 0.1621385 -2.484634 0.4287672
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] 3.095899 0.1557146 -1.111852 1.033433 -0.03502413 -1.45394 -0.9401928
[2,] 3.095899 0.1557146 -1.111852 1.033433 -0.03502413 -1.45394 -0.9401928
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] -0.08482888 0.4631771 1.962436 2.753316 -0.1729323 -1.12269 0.3745323
[2,] -0.08482888 0.4631771 1.962436 2.753316 -0.1729323 -1.12269 0.3745323
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] -1.002045 -0.6325129 0.07125262 0.191889 0.6513902 -0.7385258 1.541851
[2,] -1.002045 -0.6325129 0.07125262 0.191889 0.6513902 -0.7385258 1.541851
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] -1.319425 0.2071122 1.215167 -1.438027 0.1133666 -0.2938427 0.8099467
[2,] -1.319425 0.2071122 1.215167 -1.438027 0.1133666 -0.2938427 0.8099467
[,99] [,100]
[1,] -1.019461 -0.2103006
[2,] -1.019461 -0.2103006
>
>
> Max(tmp2)
[1] 2.376235
> Min(tmp2)
[1] -2.695844
> mean(tmp2)
[1] 0.06050638
> Sum(tmp2)
[1] 6.050638
> Var(tmp2)
[1] 1.053561
>
> rowMeans(tmp2)
[1] 2.01309454 -0.70275193 -0.36318856 1.12435595 0.80736124 1.20239144
[7] -1.01870877 1.33741275 0.21048017 0.04859221 -2.69584396 0.07783770
[13] 1.33242202 -0.38574387 1.07095977 -1.63251336 -0.93744022 -0.85755483
[19] 0.71671436 2.31881089 -0.31012526 2.13110473 -1.40951722 -0.66936861
[25] -0.43545070 1.11904071 0.31382546 -0.62403345 -1.01675730 1.57628419
[31] -0.16032917 -0.28004735 -0.31293050 -0.15189377 0.85843309 0.68384321
[37] 0.10108153 -0.61088775 0.26640700 -1.47394619 0.80872163 0.79190707
[43] 0.94866985 1.17980772 1.61834377 -0.67416684 -0.85503178 0.16265421
[49] -0.91358880 -0.21829888 -0.77628582 -2.02669668 0.05534559 -0.23397755
[55] -0.22125804 1.21949984 -0.64497329 1.10035625 2.37623453 0.86013348
[61] -0.62200555 -1.71024712 -0.32596760 -1.29473135 -0.24919434 -0.64556914
[67] 0.62917237 -0.24989534 -0.02128942 1.46921254 0.82032136 1.01713150
[73] -0.98976589 0.50939710 0.24284033 0.33759302 2.03199547 -0.28022445
[79] 0.03609157 -1.05556564 0.31894495 -0.36427655 0.43351518 -1.30674609
[85] -1.11953638 0.29218252 0.61923071 1.09085450 0.75253023 1.62241133
[91] -1.41744270 -0.10085944 -0.15849998 0.42861351 -1.90223408 -0.87389797
[97] -0.34667788 -0.82775597 0.11673376 1.32543286
> rowSums(tmp2)
[1] 2.01309454 -0.70275193 -0.36318856 1.12435595 0.80736124 1.20239144
[7] -1.01870877 1.33741275 0.21048017 0.04859221 -2.69584396 0.07783770
[13] 1.33242202 -0.38574387 1.07095977 -1.63251336 -0.93744022 -0.85755483
[19] 0.71671436 2.31881089 -0.31012526 2.13110473 -1.40951722 -0.66936861
[25] -0.43545070 1.11904071 0.31382546 -0.62403345 -1.01675730 1.57628419
[31] -0.16032917 -0.28004735 -0.31293050 -0.15189377 0.85843309 0.68384321
[37] 0.10108153 -0.61088775 0.26640700 -1.47394619 0.80872163 0.79190707
[43] 0.94866985 1.17980772 1.61834377 -0.67416684 -0.85503178 0.16265421
[49] -0.91358880 -0.21829888 -0.77628582 -2.02669668 0.05534559 -0.23397755
[55] -0.22125804 1.21949984 -0.64497329 1.10035625 2.37623453 0.86013348
[61] -0.62200555 -1.71024712 -0.32596760 -1.29473135 -0.24919434 -0.64556914
[67] 0.62917237 -0.24989534 -0.02128942 1.46921254 0.82032136 1.01713150
[73] -0.98976589 0.50939710 0.24284033 0.33759302 2.03199547 -0.28022445
[79] 0.03609157 -1.05556564 0.31894495 -0.36427655 0.43351518 -1.30674609
[85] -1.11953638 0.29218252 0.61923071 1.09085450 0.75253023 1.62241133
[91] -1.41744270 -0.10085944 -0.15849998 0.42861351 -1.90223408 -0.87389797
[97] -0.34667788 -0.82775597 0.11673376 1.32543286
> 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] 2.01309454 -0.70275193 -0.36318856 1.12435595 0.80736124 1.20239144
[7] -1.01870877 1.33741275 0.21048017 0.04859221 -2.69584396 0.07783770
[13] 1.33242202 -0.38574387 1.07095977 -1.63251336 -0.93744022 -0.85755483
[19] 0.71671436 2.31881089 -0.31012526 2.13110473 -1.40951722 -0.66936861
[25] -0.43545070 1.11904071 0.31382546 -0.62403345 -1.01675730 1.57628419
[31] -0.16032917 -0.28004735 -0.31293050 -0.15189377 0.85843309 0.68384321
[37] 0.10108153 -0.61088775 0.26640700 -1.47394619 0.80872163 0.79190707
[43] 0.94866985 1.17980772 1.61834377 -0.67416684 -0.85503178 0.16265421
[49] -0.91358880 -0.21829888 -0.77628582 -2.02669668 0.05534559 -0.23397755
[55] -0.22125804 1.21949984 -0.64497329 1.10035625 2.37623453 0.86013348
[61] -0.62200555 -1.71024712 -0.32596760 -1.29473135 -0.24919434 -0.64556914
[67] 0.62917237 -0.24989534 -0.02128942 1.46921254 0.82032136 1.01713150
[73] -0.98976589 0.50939710 0.24284033 0.33759302 2.03199547 -0.28022445
[79] 0.03609157 -1.05556564 0.31894495 -0.36427655 0.43351518 -1.30674609
[85] -1.11953638 0.29218252 0.61923071 1.09085450 0.75253023 1.62241133
[91] -1.41744270 -0.10085944 -0.15849998 0.42861351 -1.90223408 -0.87389797
[97] -0.34667788 -0.82775597 0.11673376 1.32543286
> rowMin(tmp2)
[1] 2.01309454 -0.70275193 -0.36318856 1.12435595 0.80736124 1.20239144
[7] -1.01870877 1.33741275 0.21048017 0.04859221 -2.69584396 0.07783770
[13] 1.33242202 -0.38574387 1.07095977 -1.63251336 -0.93744022 -0.85755483
[19] 0.71671436 2.31881089 -0.31012526 2.13110473 -1.40951722 -0.66936861
[25] -0.43545070 1.11904071 0.31382546 -0.62403345 -1.01675730 1.57628419
[31] -0.16032917 -0.28004735 -0.31293050 -0.15189377 0.85843309 0.68384321
[37] 0.10108153 -0.61088775 0.26640700 -1.47394619 0.80872163 0.79190707
[43] 0.94866985 1.17980772 1.61834377 -0.67416684 -0.85503178 0.16265421
[49] -0.91358880 -0.21829888 -0.77628582 -2.02669668 0.05534559 -0.23397755
[55] -0.22125804 1.21949984 -0.64497329 1.10035625 2.37623453 0.86013348
[61] -0.62200555 -1.71024712 -0.32596760 -1.29473135 -0.24919434 -0.64556914
[67] 0.62917237 -0.24989534 -0.02128942 1.46921254 0.82032136 1.01713150
[73] -0.98976589 0.50939710 0.24284033 0.33759302 2.03199547 -0.28022445
[79] 0.03609157 -1.05556564 0.31894495 -0.36427655 0.43351518 -1.30674609
[85] -1.11953638 0.29218252 0.61923071 1.09085450 0.75253023 1.62241133
[91] -1.41744270 -0.10085944 -0.15849998 0.42861351 -1.90223408 -0.87389797
[97] -0.34667788 -0.82775597 0.11673376 1.32543286
>
> colMeans(tmp2)
[1] 0.06050638
> colSums(tmp2)
[1] 6.050638
> colVars(tmp2)
[1] 1.053561
> colSd(tmp2)
[1] 1.026431
> colMax(tmp2)
[1] 2.376235
> colMin(tmp2)
[1] -2.695844
> colMedians(tmp2)
[1] 0.007401074
> colRanges(tmp2)
[,1]
[1,] -2.695844
[2,] 2.376235
>
> dataset1 <- matrix(dataset1,1,100)
>
> agree.checks(tmp,dataset1)
>
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>
>
> tmp <- createBufferedMatrix(10,10)
>
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
[1] 5.8697100 -1.7020813 2.3826006 1.2694833 -1.4098869 -4.2750612
[7] -0.2538504 -5.5899387 0.1199969 -3.0437831
> colApply(tmp,quantile)[,1]
[,1]
[1,] -0.8246067
[2,] 0.1064486
[3,] 0.6739218
[4,] 0.8785405
[5,] 2.4536454
>
> rowApply(tmp,sum)
[1] -0.4914509 -5.6134527 -1.0750348 -0.4829172 2.5048182 -2.6345559
[7] -2.5373413 -3.7402273 -4.7613809 12.1987318
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 9 7 5 8 10 10 5 9 2 4
[2,] 3 3 2 9 4 4 9 5 3 9
[3,] 5 6 4 1 9 9 7 8 8 10
[4,] 8 1 7 3 7 6 8 10 9 7
[5,] 1 10 6 5 8 7 2 3 6 8
[6,] 7 5 1 2 3 2 6 4 5 6
[7,] 10 4 10 7 2 3 4 2 7 2
[8,] 6 2 9 6 5 8 1 1 4 3
[9,] 2 9 8 10 6 5 3 6 1 5
[10,] 4 8 3 4 1 1 10 7 10 1
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -1.81173604 1.83687451 2.82204922 -1.42366101 -1.78673121 -3.16716031
[7] -4.59505549 1.90032743 -0.73499238 -3.20724527 -0.89362082 -1.79870065
[13] -2.52569934 -0.95337676 2.64301842 2.24892444 1.39162591 -1.78817268
[19] -0.02947781 -1.76953648
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.4800056
[2,] -0.3951735
[3,] -0.1690920
[4,] -0.1274765
[5,] 0.3600116
>
> rowApply(tmp,sum)
[1] -6.0008325 1.0218083 -0.4173848 -1.7160119 -6.5299255
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 4 10 7 9 16
[2,] 19 15 16 7 10
[3,] 11 16 14 15 20
[4,] 17 5 6 8 4
[5,] 16 4 12 5 3
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -1.4800056 0.8208624 -0.3182707 0.7141902 0.5736847 -0.3880034
[2,] -0.1274765 0.8095183 0.9533483 -0.4967102 -0.9335426 1.4375258
[3,] -0.3951735 0.7885503 0.7527531 -0.4459253 0.3297897 -1.3965876
[4,] -0.1690920 -0.3622778 0.3576399 -0.1701948 -0.5330569 -1.0400685
[5,] 0.3600116 -0.2197786 1.0765786 -1.0250210 -1.2236062 -1.7800266
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -0.1643254 0.7315913 -0.3524842 -0.3858066 0.20410585 -0.3582387
[2,] -1.6699018 0.1691002 -0.1695674 -2.2098233 0.26080920 -1.7481986
[3,] -1.4609899 -0.3345357 0.7633294 1.2676052 -1.60278066 -0.3315443
[4,] -1.8148959 0.9093841 -0.1033986 -0.8674552 -0.09914995 0.5216385
[5,] 0.5150575 0.4247874 -0.8728717 -1.0117654 0.34339473 0.1176424
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -1.6831912 -0.7793493 1.3087375 0.2422025 -1.9607602 -0.7078117
[2,] -0.1522707 0.2481860 1.4215854 1.4702137 0.6289387 -0.3736233
[3,] -1.7696725 1.5655727 0.7032737 1.1388802 1.8005486 -0.3611748
[4,] 1.4841245 0.5309443 -0.9331564 0.3433813 0.2173374 -0.5245550
[5,] -0.4046895 -2.5187305 0.1425782 -0.9457533 0.7055614 0.1789920
[,19] [,20]
[1,] 0.123478900 -2.141439
[2,] -0.137458881 1.641156
[3,] 0.001913004 -1.431217
[4,] -0.126769075 0.663608
[5,] 0.109358244 -0.501645
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: F:/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.8 Kilobytes.
Disk usage : 800 bytes.
>
>
>
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size: 5 5
Buffer size: 1 1
Directory: F:/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 630 bytes.
Disk usage : 200 bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size: 5 4
Buffer size: 1 1
Directory: F:/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 547 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: F:/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.8 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 -0.619534 -0.4985965 1.44603 0.498506 -0.3889318 -0.4522026 -2.639372
col8 col9 col10 col11 col12 col13 col14
row1 0.3182213 -0.05756617 0.7289603 -0.08512031 -0.02324302 1.253897 1.53855
col15 col16 col17 col18 col19 col20
row1 0.02325035 -2.298421 -0.2258469 1.158893 0.5767806 0.9218185
> tmp[,"col10"]
col10
row1 0.7289603
row2 0.2568284
row3 -0.8050303
row4 0.8403295
row5 0.1255293
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 -0.619534 -0.4985965 1.4460304 0.4985060 -0.3889318 -0.4522026 -2.639372
row5 1.055085 -2.1292887 -0.6535312 0.8558689 -0.4491285 0.2710684 3.352477
col8 col9 col10 col11 col12 col13
row1 0.3182213 -0.05756617 0.7289603 -0.08512031 -0.02324302 1.2538969
row5 -0.6993941 -0.02500154 0.1255293 -0.71301222 0.13935952 -0.8357523
col14 col15 col16 col17 col18 col19 col20
row1 1.538550 0.02325035 -2.2984210 -0.2258469 1.158893 0.5767806 0.9218185
row5 1.056247 0.10678593 0.9601967 -2.2670657 -1.146305 -1.1628990 -0.3806808
> tmp[,c("col6","col20")]
col6 col20
row1 -0.4522026 0.92181851
row2 -0.5397717 0.02554449
row3 -0.9537896 1.32457282
row4 1.1564239 -0.75597617
row5 0.2710684 -0.38068084
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -0.4522026 0.9218185
row5 0.2710684 -0.3806808
>
>
>
>
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105)
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.62167 50.5494 49.96207 51.11408 51.34031 106.0425 50.36108 50.56946
col9 col10 col11 col12 col13 col14 col15 col16
row1 48.65398 49.32652 51.12324 50.59781 49.02697 49.3875 49.52132 50.9075
col17 col18 col19 col20
row1 48.93107 51.4086 47.6384 104.7144
> tmp[,"col10"]
col10
row1 49.32652
row2 29.38708
row3 31.32891
row4 31.17365
row5 49.74311
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 50.62167 50.54940 49.96207 51.11408 51.34031 106.0425 50.36108 50.56946
row5 49.74011 50.24118 49.87668 49.09460 49.05506 106.6991 49.28263 49.73586
col9 col10 col11 col12 col13 col14 col15 col16
row1 48.65398 49.32652 51.12324 50.59781 49.02697 49.38750 49.52132 50.90750
row5 48.58605 49.74311 50.36279 50.13665 50.09761 48.77869 49.62151 49.05196
col17 col18 col19 col20
row1 48.93107 51.40860 47.63840 104.7144
row5 48.72184 48.89913 48.88025 104.7658
> tmp[,c("col6","col20")]
col6 col20
row1 106.04248 104.71439
row2 77.42002 76.29474
row3 74.68132 73.62914
row4 75.68323 75.03758
row5 106.69911 104.76580
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 106.0425 104.7144
row5 106.6991 104.7658
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 106.0425 104.7144
row5 106.6991 104.7658
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] -0.31000289
[2,] 0.02540629
[3,] 1.21910650
[4,] 0.28422801
[5,] 0.70945762
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.5876645 -0.52052014
[2,] -0.5217978 -0.02658054
[3,] -1.4704884 0.44932673
[4,] 0.7969110 0.58175440
[5,] 1.2147534 1.31461057
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] 1.9386350 0.8894463
[2,] 0.1640828 -0.3269596
[3,] -0.1178767 -0.9478521
[4,] -1.0344403 -1.3974381
[5,] 0.3954632 -0.1069867
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] 1.938635
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] 1.9386350
[2,] 0.1640828
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6]
row3 0.38265264 0.30507279 0.02569466 0.6731607 1.59787629 -0.1987621
row1 0.03309385 -0.01326439 1.12545499 -1.0281777 0.07998837 0.4427644
[,7] [,8] [,9] [,10] [,11] [,12]
row3 -0.2088102 -1.0860502 0.01933581 0.1715832 1.0638448 0.90871338
row1 0.8928773 0.1869955 0.21390079 -1.0943243 0.8311575 -0.04666709
[,13] [,14] [,15] [,16] [,17] [,18] [,19]
row3 -0.3572491 -2.358274 -1.990482 -0.8200543 1.4766317 1.8416517 -0.2930191
row1 0.9118744 1.923716 1.775819 -0.8363902 0.3376019 -0.3335374 0.2373788
[,20]
row3 0.8473182
row1 -1.0468472
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.44727 0.9508124 0.6066824 -0.5202395 1.013768 -0.8702054 0.9484401
[,8] [,9] [,10]
row2 0.4087658 1.565915 -0.1919397
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 -0.2386783 0.2600925 0.6316003 0.0887378 -0.2561741 -0.8738856 1.507102
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.3130593 -1.238231 1.134551 1.333208 0.363607 -2.713581 -0.4361689
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.2142233 0.4019487 0.5664452 -1.386412 0.475341 -0.6186732
>
>
> 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: 0x000001eb3b2f8b30>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "F:/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests\\BM21c4c43ed74b3"
[2] "F:/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests\\BM21c4c5ca22bc1"
[3] "F:/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests\\BM21c4c89136c5"
[4] "F:/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests\\BM21c4c34b15e06"
[5] "F:/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests\\BM21c4c2a95508"
[6] "F:/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests\\BM21c4c76847bf5"
[7] "F:/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests\\BM21c4c52e5697e"
[8] "F:/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests\\BM21c4c1fe968b4"
[9] "F:/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests\\BM21c4c7a21329f"
[10] "F:/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests\\BM21c4c724429a4"
[11] "F:/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests\\BM21c4c4b8c4cf1"
[12] "F:/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests\\BM21c4c15d7c93"
[13] "F:/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests\\BM21c4c4a092ad9"
[14] "F:/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests\\BM21c4c2407e33"
[15] "F:/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests\\BM21c4c74d53eb1"
>
>
> ### 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: 0x000001eb3bfff470>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x000001eb3bfff470>
Warning message:
In dir.create(new.directory) :
'F:\biocbuild\bbs-3.22-bioc\meat\BufferedMatrix.Rcheck\tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x000001eb3bfff470>
> rowMedians(tmp)
[1] 0.457257840 -0.344648754 0.683655967 0.206815867 0.359693621
[6] 0.250124333 -0.051754383 -0.231385246 0.303499864 0.351405123
[11] -0.099517490 -0.142842837 -0.256239100 0.276198963 -0.420637875
[16] 0.033458816 -0.166372222 -0.199692985 0.335985687 -0.020073280
[21] -0.336308465 -0.169675524 0.333251758 0.262073166 0.292702050
[26] -0.194712635 -0.130539855 0.042961529 -0.435013215 -0.090500459
[31] -0.477287709 -0.342423154 0.129508109 0.127178323 0.465656902
[36] 0.048440905 -0.134664668 0.078196275 -0.501351482 0.471226196
[41] 0.132205093 0.237591907 -0.338792317 0.083581669 -0.245015572
[46] -0.371322383 0.244318851 0.192688589 -0.081943233 0.028900669
[51] 0.038107938 0.130946980 -0.447666369 0.112909974 0.294976328
[56] -0.043169528 -0.637746592 -0.699472519 -0.529491982 -0.127818899
[61] 0.213372561 0.168515863 0.090887497 0.330586756 0.016001031
[66] -0.453955743 0.079354943 0.191644645 0.230584330 -0.278507026
[71] -0.018524267 -0.661625861 0.269120503 -0.116700599 -0.063184823
[76] 0.074708978 -0.123766705 -0.324359231 -0.484557817 0.228346126
[81] -0.171199492 -0.045696435 -0.271386244 -0.506999159 0.005479679
[86] -0.008503169 -0.085828740 -0.218828276 -0.170616559 0.496613526
[91] -0.311838729 -0.101495755 0.030147606 -0.599045823 0.509718853
[96] 0.605824487 0.007152088 -0.180845566 0.053905220 0.505618261
[101] -0.180277345 -0.126569061 0.625029803 0.304608877 -0.482868341
[106] -0.116934214 -0.166565141 -0.453870805 0.050898063 0.770763674
[111] 1.073515069 -0.134961861 -0.439060522 -0.728665944 -0.055950233
[116] 0.094701899 -0.045827029 -0.060401834 0.656478576 0.383795018
[121] 0.516946453 0.404094277 -0.089742566 0.140837846 -0.512422778
[126] 0.108118125 -0.176565411 0.319015183 0.103785695 -0.603794209
[131] 0.144797792 0.334548196 0.257990469 0.282534930 -0.211840968
[136] -0.030707313 0.190135208 0.211511993 -0.034757796 0.176744906
[141] -0.001951961 -0.250288360 0.155540157 -0.247496138 -0.439399790
[146] -0.001926555 -0.557238902 0.210708079 0.105500060 -0.005631493
[151] -0.040093781 -0.432220165 -0.178804302 -0.318437443 -0.176699334
[156] -0.377092790 -0.123585440 -0.582030834 0.018138439 0.059830171
[161] 0.619289271 -0.174926393 -0.193844176 0.479001327 -0.216303551
[166] 0.383827227 0.004072753 0.138619679 0.382546647 0.295740322
[171] -0.035115477 0.470872437 0.090141914 0.272186319 0.213105405
[176] -0.185237732 -0.465923261 -0.488356601 -0.403853189 0.256031660
[181] -0.371903828 -0.134688246 -0.235764041 -0.631150203 0.199103483
[186] 0.096584150 -0.306188012 -0.012347686 -0.898357108 0.347807951
[191] 0.151754044 -0.479218404 -0.209907480 0.625255452 -0.353270249
[196] -0.250702541 0.029771428 -0.321128690 -0.519494441 -0.419958541
[201] 0.134642825 0.161977070 0.496295578 0.404614834 -0.620461148
[206] -0.659752768 0.571286401 0.074217143 -0.273373308 0.713388142
[211] -0.325753253 -0.125145952 0.055105529 -0.259432838 -0.306601713
[216] -0.525940191 0.022148204 0.337858309 0.201137650 0.026349146
[221] -0.084693015 0.316801165 -0.072997768 0.185886905 -0.075495213
[226] 0.185243136 0.426548801 -0.472071557 -0.214521068 -0.198855929
>
> proc.time()
user system elapsed
3.73 15.18 119.26
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.5.1 (2025-06-13 ucrt) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64
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: 0x000001d8d62f8050>
> .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: 0x000001d8d62f8050>
> .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: 0x000001d8d62f8050>
> .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: 0x000001d8d62f8050>
> 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: 0x000001d8d62f8bf0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000001d8d62f8bf0>
> .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: 0x000001d8d62f8bf0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000001d8d62f8bf0>
> .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: 0x000001d8d62f8bf0>
> 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: 0x000001d8d62f8410>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000001d8d62f8410>
> .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: 0x000001d8d62f8410>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x000001d8d62f8410>
> .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: 0x000001d8d62f8410>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x000001d8d62f8410>
> .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: 0x000001d8d62f8410>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x000001d8d62f8410>
> .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: 0x000001d8d62f8410>
> 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: 0x000001d8d62f8e90>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x000001d8d62f8e90>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000001d8d62f8e90>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000001d8d62f8e90>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1b4b0422525e4" "BufferedMatrixFile1b4b059911524"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1b4b0422525e4" "BufferedMatrixFile1b4b059911524"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x000001d8d75f88f0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000001d8d75f88f0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x000001d8d75f88f0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x000001d8d75f88f0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x000001d8d75f88f0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x000001d8d75f88f0>
> .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: 0x000001d8d75f8bf0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000001d8d75f8bf0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x000001d8d75f8bf0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x000001d8d75f8bf0>
> 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: 0x000001d8d75f8050>
> .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: 0x000001d8d75f8050>
> rm(P)
>
> proc.time()
user system elapsed
0.28 0.09 0.64
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.5.1 (2025-06-13 ucrt) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64
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
0.34 0.09 0.40