Ben Bolstad
| Snapshot Date: 2025-08-08 13:45 -0400 (Fri, 08 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 2025-08-09 12:06 -0400 (Sat, 09 Aug 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 24.04.2 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" | 4553 |
| lconway | macOS 12.7.1 Monterey | x86_64 | 4.5.1 (2025-06-13) -- "Great Square Root" | 4595 |
| kjohnson3 | macOS 13.7.1 Ventura | arm64 | 4.5.1 Patched (2025-06-14 r88325) -- "Great Square Root" | 4537 |
| 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 24.04.2 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 13.7.1 Ventura / arm64 | OK | OK | WARNINGS | 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: 2025-08-09 00:07:01 -0400 (Sat, 09 Aug 2025) |
| EndedAt: 2025-08-09 00:09:53 -0400 (Sat, 09 Aug 2025) |
| EllapsedTime: 171.5 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
0.31 0.15 1.45
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 867355 6.7 8388608 64.0 2039181 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] "Sat Aug 9 00:07:37 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] "Sat Aug 9 00:07:38 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: 0x00000246d44f96b0>
>
>
>
> 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] "Sat Aug 9 00:08:04 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] "Sat Aug 9 00:08:11 2025"
>
> ColMode(tmp2)
<pointer: 0x00000246d44f96b0>
>
>
>
> ### 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,] 99.7742761 0.9405246 0.3538136 -0.08654952
[2,] 0.1003150 -1.2158946 -0.5258081 1.45978483
[3,] 0.9828074 0.7244732 0.8494815 2.06061103
[4,] 0.1151615 0.6195590 0.3808003 -0.59151938
> 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,] 99.7742761 0.9405246 0.3538136 0.08654952
[2,] 0.1003150 1.2158946 0.5258081 1.45978483
[3,] 0.9828074 0.7244732 0.8494815 2.06061103
[4,] 0.1151615 0.6195590 0.3808003 0.59151938
> 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,] 9.9887074 0.9698065 0.5948223 0.294193
[2,] 0.3167254 1.1026761 0.7251263 1.208216
[3,] 0.9913664 0.8511599 0.9216732 1.435483
[4,] 0.3393546 0.7871207 0.6170902 0.769103
>
> 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,] 224.66135 35.63859 31.30204 28.02848
[2,] 28.26757 37.24266 32.77707 38.54194
[3,] 35.89647 34.23607 35.06621 41.41544
[4,] 28.50871 33.49077 31.55170 33.28255
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x00000246d44f9170>
> exp(tmp5)
<pointer: 0x00000246d44f9170>
> log(tmp5,2)
<pointer: 0x00000246d44f9170>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 467.6032
> Min(tmp5)
[1] 54.42917
> mean(tmp5)
[1] 72.75853
> Sum(tmp5)
[1] 14551.71
> Var(tmp5)
[1] 856.8237
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 91.52887 70.47513 70.81678 70.37298 68.91826 72.12014 69.44935 69.08824
[9] 72.51485 72.30070
> rowSums(tmp5)
[1] 1830.577 1409.503 1416.336 1407.460 1378.365 1442.403 1388.987 1381.765
[9] 1450.297 1446.014
> rowVars(tmp5)
[1] 7892.71308 72.07961 63.49999 85.71637 46.82095 63.38331
[7] 86.56668 75.46475 86.94378 72.65222
> rowSd(tmp5)
[1] 88.840943 8.489971 7.968688 9.258314 6.842584 7.961363 9.304121
[8] 8.687045 9.324365 8.523627
> rowMax(tmp5)
[1] 467.60317 82.19454 86.20081 88.27345 83.75476 92.16366 87.60008
[8] 83.07662 85.45992 86.06855
> rowMin(tmp5)
[1] 58.33761 57.43263 59.95367 57.85234 59.74235 61.59274 56.66580 54.42917
[9] 58.11591 56.42161
>
> colMeans(tmp5)
[1] 105.36312 71.44378 69.73856 70.33111 69.79718 74.96564 68.53682
[8] 74.76463 70.16909 69.21336 74.54571 72.16537 70.52909 67.40543
[15] 76.16053 66.61042 69.70319 71.67295 69.88501 72.16960
> colSums(tmp5)
[1] 1053.6312 714.4378 697.3856 703.3111 697.9718 749.6564 685.3682
[8] 747.6463 701.6909 692.1336 745.4571 721.6537 705.2909 674.0543
[15] 761.6053 666.1042 697.0319 716.7295 698.8501 721.6960
> colVars(tmp5)
[1] 16259.68790 37.68341 24.23946 83.80881 69.21821 86.22531
[7] 67.87489 81.92828 72.97866 61.22007 68.38634 61.82363
[13] 57.57954 85.33291 81.96007 46.60996 50.84316 69.53705
[19] 98.57449 101.78367
> colSd(tmp5)
[1] 127.513481 6.138682 4.923359 9.154715 8.319748 9.285759
[7] 8.238622 9.051424 8.542755 7.824325 8.269603 7.862800
[13] 7.588118 9.237582 9.053180 6.827148 7.130439 8.338888
[19] 9.928469 10.088789
> colMax(tmp5)
[1] 467.60317 84.58173 78.72386 86.20081 82.73117 92.16366 82.19454
[8] 87.22608 82.95600 83.07662 84.49055 85.90931 83.03458 81.84125
[15] 88.27345 79.46680 80.11709 87.60008 86.29671 82.89892
> colMin(tmp5)
[1] 56.42161 63.70809 65.15109 58.33761 58.22474 59.95367 57.85234 59.94583
[9] 60.81901 58.78891 59.74235 59.57977 58.11591 57.92712 61.13183 57.43263
[17] 59.68231 59.90375 56.66580 54.42917
>
>
> ### 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] 91.52887 70.47513 70.81678 70.37298 68.91826 72.12014 69.44935 69.08824
[9] NA 72.30070
> rowSums(tmp5)
[1] 1830.577 1409.503 1416.336 1407.460 1378.365 1442.403 1388.987 1381.765
[9] NA 1446.014
> rowVars(tmp5)
[1] 7892.71308 72.07961 63.49999 85.71637 46.82095 63.38331
[7] 86.56668 75.46475 83.77442 72.65222
> rowSd(tmp5)
[1] 88.840943 8.489971 7.968688 9.258314 6.842584 7.961363 9.304121
[8] 8.687045 9.152837 8.523627
> rowMax(tmp5)
[1] 467.60317 82.19454 86.20081 88.27345 83.75476 92.16366 87.60008
[8] 83.07662 NA 86.06855
> rowMin(tmp5)
[1] 58.33761 57.43263 59.95367 57.85234 59.74235 61.59274 56.66580 54.42917
[9] NA 56.42161
>
> colMeans(tmp5)
[1] 105.36312 71.44378 69.73856 70.33111 69.79718 74.96564 68.53682
[8] 74.76463 NA 69.21336 74.54571 72.16537 70.52909 67.40543
[15] 76.16053 66.61042 69.70319 71.67295 69.88501 72.16960
> colSums(tmp5)
[1] 1053.6312 714.4378 697.3856 703.3111 697.9718 749.6564 685.3682
[8] 747.6463 NA 692.1336 745.4571 721.6537 705.2909 674.0543
[15] 761.6053 666.1042 697.0319 716.7295 698.8501 721.6960
> colVars(tmp5)
[1] 16259.68790 37.68341 24.23946 83.80881 69.21821 86.22531
[7] 67.87489 81.92828 NA 61.22007 68.38634 61.82363
[13] 57.57954 85.33291 81.96007 46.60996 50.84316 69.53705
[19] 98.57449 101.78367
> colSd(tmp5)
[1] 127.513481 6.138682 4.923359 9.154715 8.319748 9.285759
[7] 8.238622 9.051424 NA 7.824325 8.269603 7.862800
[13] 7.588118 9.237582 9.053180 6.827148 7.130439 8.338888
[19] 9.928469 10.088789
> colMax(tmp5)
[1] 467.60317 84.58173 78.72386 86.20081 82.73117 92.16366 82.19454
[8] 87.22608 NA 83.07662 84.49055 85.90931 83.03458 81.84125
[15] 88.27345 79.46680 80.11709 87.60008 86.29671 82.89892
> colMin(tmp5)
[1] 56.42161 63.70809 65.15109 58.33761 58.22474 59.95367 57.85234 59.94583
[9] NA 58.78891 59.74235 59.57977 58.11591 57.92712 61.13183 57.43263
[17] 59.68231 59.90375 56.66580 54.42917
>
> Max(tmp5,na.rm=TRUE)
[1] 467.6032
> Min(tmp5,na.rm=TRUE)
[1] 54.42917
> mean(tmp5,na.rm=TRUE)
[1] 72.81853
> Sum(tmp5,na.rm=TRUE)
[1] 14490.89
> Var(tmp5,na.rm=TRUE)
[1] 860.4275
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.52887 70.47513 70.81678 70.37298 68.91826 72.12014 69.44935 69.08824
[9] 73.13042 72.30070
> rowSums(tmp5,na.rm=TRUE)
[1] 1830.577 1409.503 1416.336 1407.460 1378.365 1442.403 1388.987 1381.765
[9] 1389.478 1446.014
> rowVars(tmp5,na.rm=TRUE)
[1] 7892.71308 72.07961 63.49999 85.71637 46.82095 63.38331
[7] 86.56668 75.46475 83.77442 72.65222
> rowSd(tmp5,na.rm=TRUE)
[1] 88.840943 8.489971 7.968688 9.258314 6.842584 7.961363 9.304121
[8] 8.687045 9.152837 8.523627
> rowMax(tmp5,na.rm=TRUE)
[1] 467.60317 82.19454 86.20081 88.27345 83.75476 92.16366 87.60008
[8] 83.07662 85.45992 86.06855
> rowMin(tmp5,na.rm=TRUE)
[1] 58.33761 57.43263 59.95367 57.85234 59.74235 61.59274 56.66580 54.42917
[9] 58.11591 56.42161
>
> colMeans(tmp5,na.rm=TRUE)
[1] 105.36312 71.44378 69.73856 70.33111 69.79718 74.96564 68.53682
[8] 74.76463 71.20799 69.21336 74.54571 72.16537 70.52909 67.40543
[15] 76.16053 66.61042 69.70319 71.67295 69.88501 72.16960
> colSums(tmp5,na.rm=TRUE)
[1] 1053.6312 714.4378 697.3856 703.3111 697.9718 749.6564 685.3682
[8] 747.6463 640.8719 692.1336 745.4571 721.6537 705.2909 674.0543
[15] 761.6053 666.1042 697.0319 716.7295 698.8501 721.6960
> colVars(tmp5,na.rm=TRUE)
[1] 16259.68790 37.68341 24.23946 83.80881 69.21821 86.22531
[7] 67.87489 81.92828 69.95878 61.22007 68.38634 61.82363
[13] 57.57954 85.33291 81.96007 46.60996 50.84316 69.53705
[19] 98.57449 101.78367
> colSd(tmp5,na.rm=TRUE)
[1] 127.513481 6.138682 4.923359 9.154715 8.319748 9.285759
[7] 8.238622 9.051424 8.364136 7.824325 8.269603 7.862800
[13] 7.588118 9.237582 9.053180 6.827148 7.130439 8.338888
[19] 9.928469 10.088789
> colMax(tmp5,na.rm=TRUE)
[1] 467.60317 84.58173 78.72386 86.20081 82.73117 92.16366 82.19454
[8] 87.22608 82.95600 83.07662 84.49055 85.90931 83.03458 81.84125
[15] 88.27345 79.46680 80.11709 87.60008 86.29671 82.89892
> colMin(tmp5,na.rm=TRUE)
[1] 56.42161 63.70809 65.15109 58.33761 58.22474 59.95367 57.85234 59.94583
[9] 62.29706 58.78891 59.74235 59.57977 58.11591 57.92712 61.13183 57.43263
[17] 59.68231 59.90375 56.66580 54.42917
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 91.52887 70.47513 70.81678 70.37298 68.91826 72.12014 69.44935 69.08824
[9] NaN 72.30070
> rowSums(tmp5,na.rm=TRUE)
[1] 1830.577 1409.503 1416.336 1407.460 1378.365 1442.403 1388.987 1381.765
[9] 0.000 1446.014
> rowVars(tmp5,na.rm=TRUE)
[1] 7892.71308 72.07961 63.49999 85.71637 46.82095 63.38331
[7] 86.56668 75.46475 NA 72.65222
> rowSd(tmp5,na.rm=TRUE)
[1] 88.840943 8.489971 7.968688 9.258314 6.842584 7.961363 9.304121
[8] 8.687045 NA 8.523627
> rowMax(tmp5,na.rm=TRUE)
[1] 467.60317 82.19454 86.20081 88.27345 83.75476 92.16366 87.60008
[8] 83.07662 NA 86.06855
> rowMin(tmp5,na.rm=TRUE)
[1] 58.33761 57.43263 59.95367 57.85234 59.74235 61.59274 56.66580 54.42917
[9] NA 56.42161
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 109.08306 71.89463 68.74020 71.14625 69.17920 74.09682 69.35717
[8] 73.57626 NaN 70.37163 74.06429 71.77209 71.90834 65.80145
[15] 75.73762 66.21250 70.81663 70.75518 69.01336 70.97745
> colSums(tmp5,na.rm=TRUE)
[1] 981.7475 647.0517 618.6618 640.3163 622.6128 666.8714 624.2145 662.1864
[9] 0.0000 633.3447 666.5786 645.9488 647.1750 592.2130 681.6385 595.9125
[17] 637.3496 636.7967 621.1202 638.7970
> colVars(tmp5,na.rm=TRUE)
[1] 18136.47255 40.10715 16.05613 86.80970 73.57424 88.51153
[7] 68.78830 76.28191 NA 53.77963 74.32732 67.81150
[13] 43.37599 67.05608 90.19296 50.65487 43.25160 68.75336
[19] 102.34875 98.51796
> colSd(tmp5,na.rm=TRUE)
[1] 134.671721 6.333021 4.007010 9.317173 8.577543 9.408057
[7] 8.293871 8.733952 NA 7.333460 8.621330 8.234774
[13] 6.586045 8.188778 9.496997 7.117223 6.576595 8.291765
[19] 10.116756 9.925621
> colMax(tmp5,na.rm=TRUE)
[1] 467.60317 84.58173 77.43754 86.20081 82.73117 92.16366 82.19454
[8] 87.22608 -Inf 83.07662 84.49055 85.90931 83.03458 81.63531
[15] 88.27345 79.46680 80.11709 87.60008 86.29671 81.75158
> colMin(tmp5,na.rm=TRUE)
[1] 56.42161 63.70809 65.15109 58.33761 58.22474 59.95367 57.85234 59.94583
[9] Inf 62.75368 59.74235 59.57977 59.13038 57.92712 61.13183 57.43263
[17] 62.00267 59.90375 56.66580 54.42917
>
>
>
>
> 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] 274.9764 275.8227 138.1728 234.2177 215.0253 136.7968 284.9020 209.9214
[9] 180.2962 149.4878
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 274.9764 275.8227 138.1728 234.2177 215.0253 136.7968 284.9020 209.9214
[9] 180.2962 149.4878
>
>
>
> copymatrix <- matrix(rnorm(200,150,15),10,20)
>
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col <- 3
> cat(which.row," ",which.col,"\n")
1 3
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
>
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
[1] -8.526513e-14 1.136868e-13 -2.131628e-14 5.684342e-14 -5.684342e-14
[6] -5.684342e-14 -1.136868e-13 0.000000e+00 -8.526513e-14 -1.136868e-13
[11] 0.000000e+00 1.136868e-13 -2.842171e-14 -2.842171e-14 4.263256e-14
[16] 5.684342e-14 -5.684342e-14 -1.421085e-14 -1.136868e-13 1.705303e-13
>
>
>
>
>
>
>
>
>
>
> ## making sure these things agree
> ##
> ## first when there is no NA
>
>
>
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+
+ if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Max")
+ }
+
+
+ if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+ stop("No agreement in Min")
+ }
+
+
+ if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+
+ cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+ cat(sum(r.matrix,na.rm=TRUE),"\n")
+ cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+
+ stop("No agreement in Sum")
+ }
+
+ if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+ stop("No agreement in mean")
+ }
+
+
+ if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+ stop("No agreement in Var")
+ }
+
+
+
+ if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowMeans")
+ }
+
+
+ if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colMeans")
+ }
+
+
+ if(any(abs(rowSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in rowSums")
+ }
+
+
+ if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+ stop("No agreement in colSums")
+ }
+
+ ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when
+ ### computing variance
+ my.Var <- function(x,na.rm=FALSE){
+ if (all(is.na(x))){
+ return(NA)
+ } else {
+ var(x,na.rm=na.rm)
+ }
+
+ }
+
+ if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in rowVars")
+ }
+
+
+ if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+ if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMax")
+ }
+
+
+
+ if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+
+ if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMin")
+ }
+
+ if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colMedian")
+ }
+
+ if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+ stop("No agreement in colRanges")
+ }
+
+
+
+ }
>
>
>
>
>
>
>
>
>
> for (rep in 1:20){
+ copymatrix <- matrix(rnorm(200,150,15),10,20)
+
+ tmp5[1:10,1:20] <- copymatrix
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ## now lets assign some NA values and check agreement
+
+ which.row <- sample(1:10,1,replace=TRUE)
+ which.col <- sample(1:20,1,replace=TRUE)
+
+ cat(which.row," ",which.col,"\n")
+
+ tmp5[which.row,which.col] <- NA
+ copymatrix[which.row,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ## make an entire row NA
+ tmp5[which.row,] <- NA
+ copymatrix[which.row,] <- NA
+
+
+ agree.checks(tmp5,copymatrix)
+
+ ### also make an entire col NA
+ tmp5[,which.col] <- NA
+ copymatrix[,which.col] <- NA
+
+ agree.checks(tmp5,copymatrix)
+
+ ### now make 1 element non NA with NA in the rest of row and column
+
+ tmp5[which.row,which.col] <- rnorm(1,150,15)
+ copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+
+ agree.checks(tmp5,copymatrix)
+ }
7 6
1 12
9 5
4 8
5 9
4 6
4 5
9 13
4 19
5 20
6 4
3 18
7 13
3 6
8 7
5 5
10 20
1 6
10 4
6 11
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] 3.488276
> Min(tmp)
[1] -3.050154
> mean(tmp)
[1] 0.2145432
> Sum(tmp)
[1] 21.45432
> Var(tmp)
[1] 1.020015
>
> rowMeans(tmp)
[1] 0.2145432
> rowSums(tmp)
[1] 21.45432
> rowVars(tmp)
[1] 1.020015
> rowSd(tmp)
[1] 1.009958
> rowMax(tmp)
[1] 3.488276
> rowMin(tmp)
[1] -3.050154
>
> colMeans(tmp)
[1] 0.378365582 -0.680806507 0.431865951 0.313294206 -1.625025388
[6] 0.313911649 1.629820842 0.328559037 -0.433710889 -0.336779181
[11] 0.612836511 1.669994255 -0.326264525 0.372878807 1.062650137
[16] 0.969572693 0.437856293 -1.016809239 0.298434067 -0.998356515
[21] -1.932141388 1.358002747 -1.431971598 0.425895526 0.817667979
[26] -0.171560678 -0.180559125 1.371359768 0.926034357 0.219910364
[31] -0.760973004 1.291716605 -1.103727721 -0.344145217 0.606040426
[36] 1.380546843 -0.112673420 -0.537852734 -0.438800043 -0.261522175
[41] 0.452859141 -0.316674085 -0.925326709 -0.251911336 -0.042343517
[46] 2.339161942 -0.922019042 0.547630573 -0.277643741 1.619551869
[51] -1.272751247 0.495103140 0.015434728 0.799190424 0.748417778
[56] -0.294719778 0.474429910 2.350526252 0.244291225 -1.596399081
[61] 0.351464939 0.740388281 0.420112894 0.592696502 0.655909165
[66] -0.580090435 0.331160355 2.440336515 -1.115787256 -0.139132339
[71] -1.395038556 0.254070548 0.917739638 3.488275666 -0.008178946
[76] 1.963062514 -0.479795883 0.545599766 1.022337242 0.549872155
[81] 0.131520545 0.766089570 0.136519054 -0.008470558 1.077944552
[86] -0.625999541 -0.465499929 -0.324634535 0.682100366 -0.534936102
[91] -1.324907625 1.605507982 0.938663771 -0.018525670 -0.249725986
[96] 0.333289399 0.854783506 -3.050154277 1.199905608 1.065505617
> colSums(tmp)
[1] 0.378365582 -0.680806507 0.431865951 0.313294206 -1.625025388
[6] 0.313911649 1.629820842 0.328559037 -0.433710889 -0.336779181
[11] 0.612836511 1.669994255 -0.326264525 0.372878807 1.062650137
[16] 0.969572693 0.437856293 -1.016809239 0.298434067 -0.998356515
[21] -1.932141388 1.358002747 -1.431971598 0.425895526 0.817667979
[26] -0.171560678 -0.180559125 1.371359768 0.926034357 0.219910364
[31] -0.760973004 1.291716605 -1.103727721 -0.344145217 0.606040426
[36] 1.380546843 -0.112673420 -0.537852734 -0.438800043 -0.261522175
[41] 0.452859141 -0.316674085 -0.925326709 -0.251911336 -0.042343517
[46] 2.339161942 -0.922019042 0.547630573 -0.277643741 1.619551869
[51] -1.272751247 0.495103140 0.015434728 0.799190424 0.748417778
[56] -0.294719778 0.474429910 2.350526252 0.244291225 -1.596399081
[61] 0.351464939 0.740388281 0.420112894 0.592696502 0.655909165
[66] -0.580090435 0.331160355 2.440336515 -1.115787256 -0.139132339
[71] -1.395038556 0.254070548 0.917739638 3.488275666 -0.008178946
[76] 1.963062514 -0.479795883 0.545599766 1.022337242 0.549872155
[81] 0.131520545 0.766089570 0.136519054 -0.008470558 1.077944552
[86] -0.625999541 -0.465499929 -0.324634535 0.682100366 -0.534936102
[91] -1.324907625 1.605507982 0.938663771 -0.018525670 -0.249725986
[96] 0.333289399 0.854783506 -3.050154277 1.199905608 1.065505617
> 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] 0.378365582 -0.680806507 0.431865951 0.313294206 -1.625025388
[6] 0.313911649 1.629820842 0.328559037 -0.433710889 -0.336779181
[11] 0.612836511 1.669994255 -0.326264525 0.372878807 1.062650137
[16] 0.969572693 0.437856293 -1.016809239 0.298434067 -0.998356515
[21] -1.932141388 1.358002747 -1.431971598 0.425895526 0.817667979
[26] -0.171560678 -0.180559125 1.371359768 0.926034357 0.219910364
[31] -0.760973004 1.291716605 -1.103727721 -0.344145217 0.606040426
[36] 1.380546843 -0.112673420 -0.537852734 -0.438800043 -0.261522175
[41] 0.452859141 -0.316674085 -0.925326709 -0.251911336 -0.042343517
[46] 2.339161942 -0.922019042 0.547630573 -0.277643741 1.619551869
[51] -1.272751247 0.495103140 0.015434728 0.799190424 0.748417778
[56] -0.294719778 0.474429910 2.350526252 0.244291225 -1.596399081
[61] 0.351464939 0.740388281 0.420112894 0.592696502 0.655909165
[66] -0.580090435 0.331160355 2.440336515 -1.115787256 -0.139132339
[71] -1.395038556 0.254070548 0.917739638 3.488275666 -0.008178946
[76] 1.963062514 -0.479795883 0.545599766 1.022337242 0.549872155
[81] 0.131520545 0.766089570 0.136519054 -0.008470558 1.077944552
[86] -0.625999541 -0.465499929 -0.324634535 0.682100366 -0.534936102
[91] -1.324907625 1.605507982 0.938663771 -0.018525670 -0.249725986
[96] 0.333289399 0.854783506 -3.050154277 1.199905608 1.065505617
> colMin(tmp)
[1] 0.378365582 -0.680806507 0.431865951 0.313294206 -1.625025388
[6] 0.313911649 1.629820842 0.328559037 -0.433710889 -0.336779181
[11] 0.612836511 1.669994255 -0.326264525 0.372878807 1.062650137
[16] 0.969572693 0.437856293 -1.016809239 0.298434067 -0.998356515
[21] -1.932141388 1.358002747 -1.431971598 0.425895526 0.817667979
[26] -0.171560678 -0.180559125 1.371359768 0.926034357 0.219910364
[31] -0.760973004 1.291716605 -1.103727721 -0.344145217 0.606040426
[36] 1.380546843 -0.112673420 -0.537852734 -0.438800043 -0.261522175
[41] 0.452859141 -0.316674085 -0.925326709 -0.251911336 -0.042343517
[46] 2.339161942 -0.922019042 0.547630573 -0.277643741 1.619551869
[51] -1.272751247 0.495103140 0.015434728 0.799190424 0.748417778
[56] -0.294719778 0.474429910 2.350526252 0.244291225 -1.596399081
[61] 0.351464939 0.740388281 0.420112894 0.592696502 0.655909165
[66] -0.580090435 0.331160355 2.440336515 -1.115787256 -0.139132339
[71] -1.395038556 0.254070548 0.917739638 3.488275666 -0.008178946
[76] 1.963062514 -0.479795883 0.545599766 1.022337242 0.549872155
[81] 0.131520545 0.766089570 0.136519054 -0.008470558 1.077944552
[86] -0.625999541 -0.465499929 -0.324634535 0.682100366 -0.534936102
[91] -1.324907625 1.605507982 0.938663771 -0.018525670 -0.249725986
[96] 0.333289399 0.854783506 -3.050154277 1.199905608 1.065505617
> colMedians(tmp)
[1] 0.378365582 -0.680806507 0.431865951 0.313294206 -1.625025388
[6] 0.313911649 1.629820842 0.328559037 -0.433710889 -0.336779181
[11] 0.612836511 1.669994255 -0.326264525 0.372878807 1.062650137
[16] 0.969572693 0.437856293 -1.016809239 0.298434067 -0.998356515
[21] -1.932141388 1.358002747 -1.431971598 0.425895526 0.817667979
[26] -0.171560678 -0.180559125 1.371359768 0.926034357 0.219910364
[31] -0.760973004 1.291716605 -1.103727721 -0.344145217 0.606040426
[36] 1.380546843 -0.112673420 -0.537852734 -0.438800043 -0.261522175
[41] 0.452859141 -0.316674085 -0.925326709 -0.251911336 -0.042343517
[46] 2.339161942 -0.922019042 0.547630573 -0.277643741 1.619551869
[51] -1.272751247 0.495103140 0.015434728 0.799190424 0.748417778
[56] -0.294719778 0.474429910 2.350526252 0.244291225 -1.596399081
[61] 0.351464939 0.740388281 0.420112894 0.592696502 0.655909165
[66] -0.580090435 0.331160355 2.440336515 -1.115787256 -0.139132339
[71] -1.395038556 0.254070548 0.917739638 3.488275666 -0.008178946
[76] 1.963062514 -0.479795883 0.545599766 1.022337242 0.549872155
[81] 0.131520545 0.766089570 0.136519054 -0.008470558 1.077944552
[86] -0.625999541 -0.465499929 -0.324634535 0.682100366 -0.534936102
[91] -1.324907625 1.605507982 0.938663771 -0.018525670 -0.249725986
[96] 0.333289399 0.854783506 -3.050154277 1.199905608 1.065505617
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0.3783656 -0.6808065 0.431866 0.3132942 -1.625025 0.3139116 1.629821
[2,] 0.3783656 -0.6808065 0.431866 0.3132942 -1.625025 0.3139116 1.629821
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.328559 -0.4337109 -0.3367792 0.6128365 1.669994 -0.3262645 0.3728788
[2,] 0.328559 -0.4337109 -0.3367792 0.6128365 1.669994 -0.3262645 0.3728788
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 1.06265 0.9695727 0.4378563 -1.016809 0.2984341 -0.9983565 -1.932141
[2,] 1.06265 0.9695727 0.4378563 -1.016809 0.2984341 -0.9983565 -1.932141
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 1.358003 -1.431972 0.4258955 0.817668 -0.1715607 -0.1805591 1.37136
[2,] 1.358003 -1.431972 0.4258955 0.817668 -0.1715607 -0.1805591 1.37136
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 0.9260344 0.2199104 -0.760973 1.291717 -1.103728 -0.3441452 0.6060404
[2,] 0.9260344 0.2199104 -0.760973 1.291717 -1.103728 -0.3441452 0.6060404
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
[1,] 1.380547 -0.1126734 -0.5378527 -0.4388 -0.2615222 0.4528591 -0.3166741
[2,] 1.380547 -0.1126734 -0.5378527 -0.4388 -0.2615222 0.4528591 -0.3166741
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
[1,] -0.9253267 -0.2519113 -0.04234352 2.339162 -0.922019 0.5476306 -0.2776437
[2,] -0.9253267 -0.2519113 -0.04234352 2.339162 -0.922019 0.5476306 -0.2776437
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
[1,] 1.619552 -1.272751 0.4951031 0.01543473 0.7991904 0.7484178 -0.2947198
[2,] 1.619552 -1.272751 0.4951031 0.01543473 0.7991904 0.7484178 -0.2947198
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
[1,] 0.4744299 2.350526 0.2442912 -1.596399 0.3514649 0.7403883 0.4201129
[2,] 0.4744299 2.350526 0.2442912 -1.596399 0.3514649 0.7403883 0.4201129
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
[1,] 0.5926965 0.6559092 -0.5800904 0.3311604 2.440337 -1.115787 -0.1391323
[2,] 0.5926965 0.6559092 -0.5800904 0.3311604 2.440337 -1.115787 -0.1391323
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
[1,] -1.395039 0.2540705 0.9177396 3.488276 -0.008178946 1.963063 -0.4797959
[2,] -1.395039 0.2540705 0.9177396 3.488276 -0.008178946 1.963063 -0.4797959
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
[1,] 0.5455998 1.022337 0.5498722 0.1315205 0.7660896 0.1365191 -0.008470558
[2,] 0.5455998 1.022337 0.5498722 0.1315205 0.7660896 0.1365191 -0.008470558
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
[1,] 1.077945 -0.6259995 -0.4654999 -0.3246345 0.6821004 -0.5349361 -1.324908
[2,] 1.077945 -0.6259995 -0.4654999 -0.3246345 0.6821004 -0.5349361 -1.324908
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
[1,] 1.605508 0.9386638 -0.01852567 -0.249726 0.3332894 0.8547835 -3.050154
[2,] 1.605508 0.9386638 -0.01852567 -0.249726 0.3332894 0.8547835 -3.050154
[,99] [,100]
[1,] 1.199906 1.065506
[2,] 1.199906 1.065506
>
>
> Max(tmp2)
[1] 2.373169
> Min(tmp2)
[1] -2.40241
> mean(tmp2)
[1] -0.1935036
> Sum(tmp2)
[1] -19.35036
> Var(tmp2)
[1] 0.9810588
>
> rowMeans(tmp2)
[1] -1.2360474688 -1.4991778652 1.2935607349 -0.3750388853 -0.6476442913
[6] 0.1119763814 0.5886365670 -0.5246527064 1.7613110723 -0.9550866166
[11] -0.2035181720 0.4054678382 -0.0826533311 0.0023421527 -1.5941499322
[16] -1.0721914942 0.2848034230 -2.1581523065 -0.2007018316 -2.0383741838
[21] 0.6207500426 0.0537438174 0.8505100349 -0.7524662888 0.2244342028
[26] -1.0753184282 0.5007868880 -0.0001184787 -0.8133684072 -0.2679262959
[31] -0.1707417308 -0.5324651577 -1.6161263786 -0.3863351270 -1.6694545405
[36] 1.8164236623 -1.6063442403 -1.2316660242 1.1896918278 -1.8715083821
[41] -0.8735794051 0.4925767948 0.1009475273 -2.4024104317 -0.8002304407
[46] 0.7245554839 0.2862081335 -0.0075983851 2.3731692629 1.5135662378
[51] 0.0362379507 -0.1999243035 1.1143971268 -0.1023327489 -0.9665910506
[56] 0.3855139148 -1.2577760315 -1.5157283504 -0.4107858311 0.4235314671
[61] 0.2063234237 -0.4796168342 1.2264640848 0.2157987803 0.2605899295
[66] 0.1614668404 -0.3048278480 -0.7001744460 0.6033121752 -0.5781818861
[71] 1.3913788925 0.5512213091 -0.1936726136 -1.5700293700 0.9071717753
[76] -0.5011117341 1.1106732386 -0.6456136770 0.2926270646 0.2267234358
[81] -0.0857251254 -1.3948050274 -1.3956860858 -1.0886919395 0.8650176820
[86] 0.7513640610 -1.9809513209 1.2470488004 -0.7688684270 0.9620601855
[91] -1.4541062095 0.2227460751 -0.3800202519 -0.7692623240 0.3339499872
[96] -2.0533381184 0.1563965852 1.0851400581 -0.1597676050 0.3396584329
> rowSums(tmp2)
[1] -1.2360474688 -1.4991778652 1.2935607349 -0.3750388853 -0.6476442913
[6] 0.1119763814 0.5886365670 -0.5246527064 1.7613110723 -0.9550866166
[11] -0.2035181720 0.4054678382 -0.0826533311 0.0023421527 -1.5941499322
[16] -1.0721914942 0.2848034230 -2.1581523065 -0.2007018316 -2.0383741838
[21] 0.6207500426 0.0537438174 0.8505100349 -0.7524662888 0.2244342028
[26] -1.0753184282 0.5007868880 -0.0001184787 -0.8133684072 -0.2679262959
[31] -0.1707417308 -0.5324651577 -1.6161263786 -0.3863351270 -1.6694545405
[36] 1.8164236623 -1.6063442403 -1.2316660242 1.1896918278 -1.8715083821
[41] -0.8735794051 0.4925767948 0.1009475273 -2.4024104317 -0.8002304407
[46] 0.7245554839 0.2862081335 -0.0075983851 2.3731692629 1.5135662378
[51] 0.0362379507 -0.1999243035 1.1143971268 -0.1023327489 -0.9665910506
[56] 0.3855139148 -1.2577760315 -1.5157283504 -0.4107858311 0.4235314671
[61] 0.2063234237 -0.4796168342 1.2264640848 0.2157987803 0.2605899295
[66] 0.1614668404 -0.3048278480 -0.7001744460 0.6033121752 -0.5781818861
[71] 1.3913788925 0.5512213091 -0.1936726136 -1.5700293700 0.9071717753
[76] -0.5011117341 1.1106732386 -0.6456136770 0.2926270646 0.2267234358
[81] -0.0857251254 -1.3948050274 -1.3956860858 -1.0886919395 0.8650176820
[86] 0.7513640610 -1.9809513209 1.2470488004 -0.7688684270 0.9620601855
[91] -1.4541062095 0.2227460751 -0.3800202519 -0.7692623240 0.3339499872
[96] -2.0533381184 0.1563965852 1.0851400581 -0.1597676050 0.3396584329
> rowVars(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowSd(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowMax(tmp2)
[1] -1.2360474688 -1.4991778652 1.2935607349 -0.3750388853 -0.6476442913
[6] 0.1119763814 0.5886365670 -0.5246527064 1.7613110723 -0.9550866166
[11] -0.2035181720 0.4054678382 -0.0826533311 0.0023421527 -1.5941499322
[16] -1.0721914942 0.2848034230 -2.1581523065 -0.2007018316 -2.0383741838
[21] 0.6207500426 0.0537438174 0.8505100349 -0.7524662888 0.2244342028
[26] -1.0753184282 0.5007868880 -0.0001184787 -0.8133684072 -0.2679262959
[31] -0.1707417308 -0.5324651577 -1.6161263786 -0.3863351270 -1.6694545405
[36] 1.8164236623 -1.6063442403 -1.2316660242 1.1896918278 -1.8715083821
[41] -0.8735794051 0.4925767948 0.1009475273 -2.4024104317 -0.8002304407
[46] 0.7245554839 0.2862081335 -0.0075983851 2.3731692629 1.5135662378
[51] 0.0362379507 -0.1999243035 1.1143971268 -0.1023327489 -0.9665910506
[56] 0.3855139148 -1.2577760315 -1.5157283504 -0.4107858311 0.4235314671
[61] 0.2063234237 -0.4796168342 1.2264640848 0.2157987803 0.2605899295
[66] 0.1614668404 -0.3048278480 -0.7001744460 0.6033121752 -0.5781818861
[71] 1.3913788925 0.5512213091 -0.1936726136 -1.5700293700 0.9071717753
[76] -0.5011117341 1.1106732386 -0.6456136770 0.2926270646 0.2267234358
[81] -0.0857251254 -1.3948050274 -1.3956860858 -1.0886919395 0.8650176820
[86] 0.7513640610 -1.9809513209 1.2470488004 -0.7688684270 0.9620601855
[91] -1.4541062095 0.2227460751 -0.3800202519 -0.7692623240 0.3339499872
[96] -2.0533381184 0.1563965852 1.0851400581 -0.1597676050 0.3396584329
> rowMin(tmp2)
[1] -1.2360474688 -1.4991778652 1.2935607349 -0.3750388853 -0.6476442913
[6] 0.1119763814 0.5886365670 -0.5246527064 1.7613110723 -0.9550866166
[11] -0.2035181720 0.4054678382 -0.0826533311 0.0023421527 -1.5941499322
[16] -1.0721914942 0.2848034230 -2.1581523065 -0.2007018316 -2.0383741838
[21] 0.6207500426 0.0537438174 0.8505100349 -0.7524662888 0.2244342028
[26] -1.0753184282 0.5007868880 -0.0001184787 -0.8133684072 -0.2679262959
[31] -0.1707417308 -0.5324651577 -1.6161263786 -0.3863351270 -1.6694545405
[36] 1.8164236623 -1.6063442403 -1.2316660242 1.1896918278 -1.8715083821
[41] -0.8735794051 0.4925767948 0.1009475273 -2.4024104317 -0.8002304407
[46] 0.7245554839 0.2862081335 -0.0075983851 2.3731692629 1.5135662378
[51] 0.0362379507 -0.1999243035 1.1143971268 -0.1023327489 -0.9665910506
[56] 0.3855139148 -1.2577760315 -1.5157283504 -0.4107858311 0.4235314671
[61] 0.2063234237 -0.4796168342 1.2264640848 0.2157987803 0.2605899295
[66] 0.1614668404 -0.3048278480 -0.7001744460 0.6033121752 -0.5781818861
[71] 1.3913788925 0.5512213091 -0.1936726136 -1.5700293700 0.9071717753
[76] -0.5011117341 1.1106732386 -0.6456136770 0.2926270646 0.2267234358
[81] -0.0857251254 -1.3948050274 -1.3956860858 -1.0886919395 0.8650176820
[86] 0.7513640610 -1.9809513209 1.2470488004 -0.7688684270 0.9620601855
[91] -1.4541062095 0.2227460751 -0.3800202519 -0.7692623240 0.3339499872
[96] -2.0533381184 0.1563965852 1.0851400581 -0.1597676050 0.3396584329
>
> colMeans(tmp2)
[1] -0.1935036
> colSums(tmp2)
[1] -19.35036
> colVars(tmp2)
[1] 0.9810588
> colSd(tmp2)
[1] 0.9904841
> colMax(tmp2)
[1] 2.373169
> colMin(tmp2)
[1] -2.40241
> colMedians(tmp2)
[1] -0.1310502
> colRanges(tmp2)
[,1]
[1,] -2.402410
[2,] 2.373169
>
> 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] 2.305369 3.182852 1.298768 -3.617867 -2.538633 -3.234432 2.755523
[8] -1.331573 1.524517 3.909332
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.0882051
[2,] -0.1904306
[3,] 0.2234304
[4,] 0.4947568
[5,] 2.0205774
>
> rowApply(tmp,sum)
[1] 2.1954364 -1.9132155 3.0648777 1.3594272 1.0373822 -0.6582862
[7] 3.2943336 -1.8687813 -0.7704604 -1.4868583
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 5 9 2 4 8 6 10 8 4 7
[2,] 7 10 10 3 3 8 2 7 2 9
[3,] 10 4 3 10 5 7 9 9 1 10
[4,] 4 8 1 8 10 4 1 2 3 1
[5,] 6 2 4 1 4 2 8 5 9 3
[6,] 1 5 8 9 1 1 4 1 5 5
[7,] 2 7 5 7 9 10 5 3 6 6
[8,] 3 1 7 2 6 3 3 10 10 4
[9,] 9 3 6 5 7 5 6 4 7 8
[10,] 8 6 9 6 2 9 7 6 8 2
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] -4.0791330 -2.5470530 -0.5214076 -0.8485810 2.0923133 0.1030399
[7] 2.7784061 3.6704245 -0.2099510 -0.5157165 1.2023964 0.5893615
[13] 3.6733899 -0.5153520 -4.1487039 2.8830473 0.6873637 0.1324985
[19] -0.7699704 0.8595896
> colApply(tmp,quantile)[,1]
[,1]
[1,] -2.67661264
[2,] -1.28400499
[3,] -0.34120907
[4,] -0.03829339
[5,] 0.26098713
>
> rowApply(tmp,sum)
[1] 3.28208296 -0.02768923 3.43293192 -3.75553920 1.58417594
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 7 2 9 9 1
[2,] 17 8 1 14 2
[3,] 18 4 19 1 10
[4,] 4 3 15 8 11
[5,] 9 9 7 19 14
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] -0.03829339 1.22498070 1.2739715 -0.4422599 -0.0004827283 -0.4063697
[2,] -1.28400499 -0.06001312 -0.9685496 -1.0772437 0.0425808250 -2.0900293
[3,] 0.26098713 -2.36808242 1.4626039 0.8630546 -0.2588258086 0.6641325
[4,] -0.34120907 0.07902208 -2.1947203 -0.3673802 1.6361031821 -0.7721118
[5,] -2.67661264 -1.42296028 -0.0947130 0.1752481 0.6729378599 2.7074182
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] 0.2945975 1.3722089 -1.6190640 0.5061440 -0.5662210 0.14178686
[2,] 0.4365026 1.0897820 1.1897935 0.6477911 0.6637353 0.69092345
[3,] 0.8724013 -0.7567646 0.2634975 -0.9278522 1.4238839 0.06322443
[4,] 0.2611864 1.7877979 -0.2549422 -0.2252391 -0.1898885 -1.05084931
[5,] 0.9137184 0.1774004 0.2107643 -0.5165603 -0.1291133 0.74427606
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] 1.4157896 -0.1872719 -1.2271034 0.1255084 -0.01323803 0.21521095
[2,] 0.6318417 0.1746781 -0.7180584 -0.1239286 1.24224017 0.06153019
[3,] 1.8305281 0.4284396 -1.0399550 0.5580177 -1.07961710 1.33986733
[4,] 0.1452510 -1.9233714 -0.9903822 1.1351658 -0.30475086 -0.68307471
[5,] -0.3500205 0.9921736 -0.1732048 1.1882840 0.84272951 -0.80103531
[,19] [,20]
[1,] 0.07808596 1.1341026
[2,] -0.78630375 0.2090434
[3,] -0.71966952 0.5530607
[4,] 1.36025041 -0.8623962
[5,] -0.70233349 -0.1742209
>
>
> 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 : 629 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 : 546 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 -0.2621484 -0.3654102 -0.546369 0.1773965 -0.7852201 -1.24969 1.782616
col8 col9 col10 col11 col12 col13 col14
row1 -0.2438102 1.762912 0.432736 0.6386464 0.5274045 0.9723266 -0.8552122
col15 col16 col17 col18 col19 col20
row1 -0.8374509 1.548154 2.156479 -0.02839292 0.5281973 0.1641054
> tmp[,"col10"]
col10
row1 0.4327360
row2 -0.2335032
row3 0.4007973
row4 -0.2315592
row5 0.8175095
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6
row1 -0.2621484 -0.3654102 -0.5463690 0.1773965 -0.7852201 -1.2496905
row5 0.5000589 0.5438590 0.7306068 -0.9673942 -0.5052409 0.9656341
col7 col8 col9 col10 col11 col12 col13
row1 1.7826160 -0.2438102 1.7629124 0.4327360 0.6386464 0.5274045 0.9723266
row5 -0.6109394 0.9256809 0.9465255 0.8175095 -0.7186366 0.9913833 0.2222469
col14 col15 col16 col17 col18 col19 col20
row1 -0.8552122 -0.8374509 1.5481544 2.156479 -0.02839292 0.5281973 0.1641054
row5 -0.9146785 0.8718493 0.6769968 -0.304821 0.87875983 -0.4543623 1.5445801
> tmp[,c("col6","col20")]
col6 col20
row1 -1.24969045 0.1641054
row2 -0.03525355 0.1407463
row3 -0.56688291 0.3243146
row4 -0.60164469 -2.4396175
row5 0.96563411 1.5445801
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -1.2496905 0.1641054
row5 0.9656341 1.5445801
>
>
>
>
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")] <- rnorm(4,mean=105)
>
> tmp["row1",]
col1 col2 col3 col4 col5 col6 col7 col8
row1 51.08468 50.51032 49.03734 50.38336 50.88941 105.5663 49.58607 49.80753
col9 col10 col11 col12 col13 col14 col15 col16
row1 47.7797 50.4125 50.62635 51.10863 48.68706 50.92912 52.37355 50.09712
col17 col18 col19 col20
row1 51.01081 49.63176 49.43556 103.4447
> tmp[,"col10"]
col10
row1 50.41250
row2 28.72286
row3 29.53091
row4 30.42627
row5 49.70401
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 51.08468 50.51032 49.03734 50.38336 50.88941 105.5663 49.58607 49.80753
row5 49.00535 51.50061 50.48512 49.89135 50.79957 105.8654 49.65806 49.82336
col9 col10 col11 col12 col13 col14 col15 col16
row1 47.77970 50.41250 50.62635 51.10863 48.68706 50.92912 52.37355 50.09712
row5 51.26354 49.70401 51.01737 51.03559 51.49866 50.45465 50.39078 49.76934
col17 col18 col19 col20
row1 51.01081 49.63176 49.43556 103.4447
row5 49.89389 49.72442 49.02067 105.2243
> tmp[,c("col6","col20")]
col6 col20
row1 105.56627 103.44465
row2 75.68684 74.66068
row3 76.24470 75.18321
row4 73.66846 74.38804
row5 105.86542 105.22430
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.5663 103.4447
row5 105.8654 105.2243
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.5663 103.4447
row5 105.8654 105.2243
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 1.2511284
[2,] 0.6476086
[3,] 0.2078933
[4,] -1.3602460
[5,] -0.2507328
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.1248303 1.46682719
[2,] -0.5254832 1.56871835
[3,] -0.4637942 -2.07429760
[4,] -0.7699991 0.03908203
[5,] 0.1640341 0.39007517
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -1.15361819 -0.5335676
[2,] 0.06174931 2.3004789
[3,] -0.49289724 0.2052230
[4,] 0.04615031 -1.2160805
[5,] 0.33652315 -1.5298917
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -1.153618
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -1.15361819
[2,] 0.06174931
>
>
>
> 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 0.03463466 0.4571691 -0.08596694 0.47757813 -0.8868315 0.45263076
row1 -0.51073190 0.1261284 0.26193726 0.06021655 -0.1758335 -0.04255789
[,7] [,8] [,9] [,10] [,11] [,12] [,13]
row3 -0.2069474 -1.265807 -0.6522688 -0.171931 1.1006855 -1.749679 0.7133206
row1 1.0070237 0.201202 -0.5790946 0.666800 0.2162551 -1.270426 -1.4423590
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
row3 0.9316027 -0.4366056 -0.5141174 -0.4052736 0.3642961 -1.3840129 -1.014435
row1 -1.6373853 -0.2115269 0.6658202 0.9984346 0.1276461 -0.2342116 1.872170
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 1.051992 1.02313 0.9721879 1.189518 0.08573199 -1.292795 -1.402221
[,8] [,9] [,10]
row2 -0.3336427 -0.7365037 -0.03666834
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.4670762 -0.5723964 0.4913136 -0.6672081 1.002682 -1.686422 0.1995
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 0.2584657 0.4043035 -0.5315823 -2.36771 1.430762 -1.306303 0.1689972
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.4587195 0.4013368 0.8491401 0.2012955 0.4801484 -0.1588016
>
>
> 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: 0x00000246d44f91d0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "F:/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests\\BM19cd4a7e60b"
[2] "F:/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests\\BM19cd44b824039"
[3] "F:/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests\\BM19cd4a74b8d"
[4] "F:/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests\\BM19cd41e104590"
[5] "F:/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests\\BM19cd410a7e8b"
[6] "F:/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests\\BM19cd44b9733b6"
[7] "F:/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests\\BM19cd41345bc7"
[8] "F:/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests\\BM19cd47fe46114"
[9] "F:/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests\\BM19cd4419d1da6"
[10] "F:/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests\\BM19cd432d250e6"
[11] "F:/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests\\BM19cd4118e23d8"
[12] "F:/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests\\BM19cd4416337fa"
[13] "F:/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests\\BM19cd44140e3b"
[14] "F:/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests\\BM19cd41d0f3eb4"
[15] "F:/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests\\BM19cd421134efd"
>
>
> ### 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: 0x00000246d44f9dd0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x00000246d44f9dd0>
Warning message:
In dir.create(new.directory) :
'F:\biocbuild\bbs-3.22-bioc\meat\BufferedMatrix.Rcheck\tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x00000246d44f9dd0>
> rowMedians(tmp)
[1] -0.1062727303 0.3483936980 0.0942004423 0.4027686862 0.3850933130
[6] 0.0823381073 0.3393363041 0.0088851513 -0.2506812040 -0.5284442775
[11] -0.1068099755 -0.3426190300 -0.1293096021 0.3573117346 -0.0507496902
[16] 0.4651860988 0.1214206024 0.0180469348 0.2498829592 -0.0648047301
[21] -0.0150241445 0.1431433219 0.2812788553 -0.0164345309 -0.3884466203
[26] -0.3734427734 0.6367315803 0.2046948813 -0.5712516977 -0.2905204406
[31] -0.6186966239 0.4291838749 0.4660002044 -0.5227366615 -0.0264638554
[36] 0.4654700038 0.1315373040 0.0114106760 -0.0035913569 -0.0485849407
[41] -0.2290664532 0.2468036040 0.2284555051 -0.3301296885 -0.0291980731
[46] -0.3139640713 -0.4529554860 -0.0083956965 0.1218033130 -0.1764800088
[51] -0.4513382186 -0.3354390612 -0.0103974996 -0.0387303816 -0.0947697742
[56] 0.1177149192 -0.3736138206 0.0599165336 0.1946016559 -0.0744049518
[61] 0.0226114886 0.4223253305 0.1432034735 -0.2270505108 -0.2165072410
[66] 0.2615319028 -0.0702044621 -0.2062473588 0.8901533406 -0.6705095070
[71] 0.2074011356 0.1713110493 -0.5770351923 -0.3982444786 0.3918983979
[76] -0.3032917447 -0.2823010015 -0.1056686373 0.1650987986 0.3182415093
[81] 0.7010431842 -0.1990852320 0.0527733566 -0.7349606301 0.0468434471
[86] 0.1931963120 0.0162886112 0.2962493708 -0.1243062780 -0.0636939148
[91] 0.3980336580 -0.1748810172 -0.0509484142 -0.2020222553 0.0974538060
[96] 0.5218590261 0.3315232375 -0.0003862368 -0.0061993539 0.1743533397
[101] 0.0152774604 0.1936417412 -0.0821248407 0.3257744836 -0.2387378731
[106] -0.6828758602 -0.3242402014 0.5245470617 0.1632742044 0.3645630667
[111] -0.4853903248 0.3112267311 0.4810774595 0.2646624170 0.0287541931
[116] 0.2660683100 -0.1357980996 -0.4926083477 -0.1691588238 -0.4221719202
[121] -0.2429397920 0.0126527794 0.1964399124 -0.0806522485 0.0604592134
[126] 0.2691248723 0.2940799526 -0.2630841811 0.4122000241 -0.1119905430
[131] 0.0699085270 0.4210396738 0.1459630375 -0.4744084084 -0.2225633051
[136] -0.0081435579 -0.6155301175 0.7841840843 0.1254159028 0.1894528181
[141] 0.1482154712 0.3835069381 0.1610552236 -0.1532286421 -0.1333775073
[146] 0.1750359529 0.0501442638 -0.5243054041 0.0235529121 -0.3218616074
[151] -0.0190224782 -0.3630749477 -0.2861918006 0.4641048144 0.4054182812
[156] -0.6274190756 0.2001292674 -0.2431991820 -0.7876453736 -0.4259417889
[161] -0.1497854521 -0.0110618315 0.0876120391 0.3611716880 -0.1246577260
[166] 0.8948088865 0.3238788161 0.0285974952 0.3919822610 0.2077627632
[171] -0.1968960270 -0.3509823451 0.5619242385 0.7465179407 -0.6657196136
[176] -0.5284170180 0.1165190116 -0.3564351938 -0.4339916403 -0.2099182574
[181] 0.1818137178 0.0715776907 -0.1545329613 0.1781650209 -0.3129167047
[186] 0.1600808746 -0.4314338576 0.1089322716 0.1148234933 0.1004807050
[191] -0.0457843375 0.2167076428 0.5495612698 0.0610423268 0.1209685647
[196] 0.1824517960 -0.5458637702 0.1113842698 -0.1836243044 0.6518199631
[201] 0.0182321028 -0.0847756150 0.4359381265 0.3519789223 0.2517695964
[206] -0.2093920868 -0.0546078246 -0.1873746934 -0.0497221942 0.0800963972
[211] 0.1918639470 0.0754862824 0.4957081333 0.1841855286 0.3323650039
[216] -0.2328155308 -0.2411860413 0.0727824438 -0.3416608974 0.3606615631
[221] -0.6865963660 -0.2382273541 0.2452061891 -0.5067771827 0.2641410692
[226] 0.2316510958 0.2797539107 -0.3688068137 0.5309031689 -0.4348677843
>
> proc.time()
user system elapsed
3.73 13.87 130.51
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: 0x000002810b8f8950>
> .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: 0x000002810b8f8950>
> .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: 0x000002810b8f8950>
> .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: 0x000002810b8f8950>
> 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: 0x000002810b8f8530>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000002810b8f8530>
> .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: 0x000002810b8f8530>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000002810b8f8530>
> .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: 0x000002810b8f8530>
> 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: 0x000002810b8f8890>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000002810b8f8890>
> .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: 0x000002810b8f8890>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x000002810b8f8890>
> .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: 0x000002810b8f8890>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x000002810b8f8890>
> .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: 0x000002810b8f8890>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x000002810b8f8890>
> .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: 0x000002810b8f8890>
> 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: 0x000002810b8f8d10>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x000002810b8f8d10>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000002810b8f8d10>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000002810b8f8d10>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile141f8219327d9" "BufferedMatrixFile141f84afa4897"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile141f8219327d9" "BufferedMatrixFile141f84afa4897"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x000002810b8f8e90>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000002810b8f8e90>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x000002810b8f8e90>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x000002810b8f8e90>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x000002810b8f8e90>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x000002810b8f8e90>
> .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: 0x000002810ddffad0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x000002810ddffad0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x000002810ddffad0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x000002810ddffad0>
> 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: 0x000002810ddff110>
> .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: 0x000002810ddff110>
> rm(P)
>
> proc.time()
user system elapsed
0.23 0.12 0.71
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.
Type 'q()' to quit R.
> library(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());
Attaching package: 'BufferedMatrix'
The following objects are masked from 'package:base':
colMeans, colSums, rowMeans, rowSums
>
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100 0
> buffer.dim(Temp)
[1] 1 1
>
>
> proc.time()
user system elapsed
0.25 0.09 0.34