Ben Bolstad
| Snapshot Date: 2025-03-31 13:00 -0400 (Mon, 31 Mar 2025) |
| git_url: https://git.bioconductor.org/packages/BufferedMatrix |
| git_branch: RELEASE_3_20 |
| git_last_commit: 32b6f6a |
| git_last_commit_date: 2024-10-29 09:27:20 -0400 (Tue, 29 Oct 2024) |
| Back to Multiple platform build/check report for BioC 3.20: simplified long |
|
This page was generated on 2025-04-02 19:29 -0400 (Wed, 02 Apr 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 24.04.1 LTS) | x86_64 | 4.4.3 (2025-02-28) -- "Trophy Case" | 4764 |
| palomino8 | Windows Server 2022 Datacenter | x64 | 4.4.3 (2025-02-28 ucrt) -- "Trophy Case" | 4495 |
| merida1 | macOS 12.7.5 Monterey | x86_64 | 4.4.3 (2025-02-28) -- "Trophy Case" | 4522 |
| kjohnson1 | macOS 13.6.6 Ventura | arm64 | 4.4.3 (2025-02-28) -- "Trophy Case" | 4449 |
| taishan | Linux (openEuler 24.03 LTS) | aarch64 | 4.4.3 (2025-02-28) -- "Trophy Case" | 4426 |
| 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 251/2289 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| BufferedMatrix 1.70.0 (landing page) Ben Bolstad
| nebbiolo2 | Linux (Ubuntu 24.04.1 LTS) / x86_64 | OK | OK | OK | | ||||||||
| palomino8 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | | ||||||||
| merida1 | macOS 12.7.5 Monterey / x86_64 | OK | OK | WARNINGS | OK | | ||||||||
| kjohnson1 | macOS 13.6.6 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: 1.70.0 |
| Command: F:\biocbuild\bbs-3.20-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:BufferedMatrix.install-out.txt --library=F:\biocbuild\bbs-3.20-bioc\R\library --no-vignettes --timings BufferedMatrix_1.70.0.tar.gz |
| StartedAt: 2025-03-31 23:37:49 -0400 (Mon, 31 Mar 2025) |
| EndedAt: 2025-03-31 23:40:12 -0400 (Mon, 31 Mar 2025) |
| EllapsedTime: 142.4 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: BufferedMatrix.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### F:\biocbuild\bbs-3.20-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:BufferedMatrix.install-out.txt --library=F:\biocbuild\bbs-3.20-bioc\R\library --no-vignettes --timings BufferedMatrix_1.70.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory 'F:/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck'
* using R version 4.4.3 (2025-02-28 ucrt)
* using platform: x86_64-w64-mingw32
* R was compiled by
gcc.exe (GCC) 13.3.0
GNU Fortran (GCC) 13.3.0
* 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 '1.70.0'
* 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) 13.3.0'
* 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-3.20-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-3.20-bioc/meat/BufferedMatrix.Rcheck/00check.log'
for details.
BufferedMatrix.Rcheck/00install.out
##############################################################################
##############################################################################
###
### Running command:
###
### F:\biocbuild\bbs-3.20-bioc\R\bin\R.exe CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################
* installing to library 'F:/biocbuild/bbs-3.20-bioc/R/library'
* installing *source* package 'BufferedMatrix' ...
** using staged installation
** libs
using C compiler: 'gcc.exe (GCC) 13.3.0'
gcc -I"F:/biocbuild/bbs-3.20-bioc/R/include" -DNDEBUG -I"C:/rtools44/x86_64-w64-mingw32.static.posix/include" -O2 -Wall -mfpmath=sse -msse2 -mstackrealign -c RBufferedMatrix.c -o RBufferedMatrix.o
gcc -I"F:/biocbuild/bbs-3.20-bioc/R/include" -DNDEBUG -I"C:/rtools44/x86_64-w64-mingw32.static.posix/include" -O2 -Wall -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-3.20-bioc/R/include" -DNDEBUG -I"C:/rtools44/x86_64-w64-mingw32.static.posix/include" -O2 -Wall -mfpmath=sse -msse2 -mstackrealign -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
gcc -I"F:/biocbuild/bbs-3.20-bioc/R/include" -DNDEBUG -I"C:/rtools44/x86_64-w64-mingw32.static.posix/include" -O2 -Wall -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:/rtools44/x86_64-w64-mingw32.static.posix/lib/x64 -LC:/rtools44/x86_64-w64-mingw32.static.posix/lib -LF:/biocbuild/bbs-3.20-bioc/R/bin/x64 -lR
installing to F:/biocbuild/bbs-3.20-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 4.4.3 (2025-02-28 ucrt) -- "Trophy Case"
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
0.29 0.12 0.90
BufferedMatrix.Rcheck/tests/objectTesting.Rout
R version 4.4.3 (2025-02-28 ucrt) -- "Trophy Case"
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-3.20-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 467958 25.0 1020317 54.5 633411 33.9
Vcells 853502 6.6 8388608 64.0 2003112 15.3
>
>
>
>
> ##
> ## 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] "Mon Mar 31 23:38:18 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] "Mon Mar 31 23:38:19 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: 0x00000165cdeff530>
>
>
>
> 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] "Mon Mar 31 23:38:39 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] "Mon Mar 31 23:38:46 2025"
>
> ColMode(tmp2)
<pointer: 0x00000165cdeff530>
>
>
>
> ### Now testing assignments
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,1)
+
+ new.data <- rnorm(20)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,] <- new.data
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,1)
+ new.data <- rnorm(10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[,which.col] <- new.data
+ test.matrix[,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.col <- which.col
+ }
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ new.data <- matrix(rnorm(50),5,10)
+ tmp2[which.row,] <- new.data
+ test.matrix[which.row,]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ }
>
>
>
>
>
> for (rep in 1:nreps){
+ which.row <- sample(1:10,5,replace=TRUE)
+ which.col <- sample(1:20,5,replace=TRUE)
+ new.data <- matrix(rnorm(25),5,5)
+ tmp2[which.row,which.col] <- new.data
+ test.matrix[which.row,which.col]<- new.data
+
+ if (rep > 1){
+ if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+ cat("incorrect agreement")
+ break;
+ }
+ }
+ prev.row <- which.row
+ prev.col <- which.col
+ }
>
>
>
>
> ###
> ###
> ### testing some more functions
> ###
>
>
>
> ## duplication function
> tmp5 <- duplicate(tmp2)
>
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
>
> if (tmp5[1,1] == tmp2[1,1]){
+ stop("Problem with duplication")
+ }
>
>
>
>
> ### testing elementwise applying of functions
>
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 100.2753444 1.057698 -0.54338440 0.1033197
[2,] -2.2164523 -1.194199 -0.52895206 -0.8488219
[3,] 0.7428227 -1.036740 -0.08428367 0.4850529
[4,] -0.5901742 -1.678442 -1.37244245 -0.2871698
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: F:/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 100.2753444 1.057698 0.54338440 0.1033197
[2,] 2.2164523 1.194199 0.52895206 0.8488219
[3,] 0.7428227 1.036740 0.08428367 0.4850529
[4,] 0.5901742 1.678442 1.37244245 0.2871698
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size: 10 20
Buffer size: 1 1
Directory: F:/biocbuild/bbs-3.20-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,] 10.0137578 1.028444 0.7371461 0.3214339
[2,] 1.4887754 1.092794 0.7272909 0.9213153
[3,] 0.8618716 1.018204 0.2903165 0.6964574
[4,] 0.7682280 1.295547 1.1715129 0.5358823
>
> 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-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 1.9 Kilobytes.
Disk usage : 1.6 Kilobytes.
> tmp5[1:4,1:4]
[,1] [,2] [,3] [,4]
[1,] 225.41292 36.34214 32.91485 28.31766
[2,] 42.10421 37.12214 32.80186 35.06197
[3,] 34.36154 36.21878 27.98745 32.44963
[4,] 33.27245 39.63391 38.08757 30.64599
>
>
>
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x00000165cdeff6b0>
> exp(tmp5)
<pointer: 0x00000165cdeff6b0>
> log(tmp5,2)
<pointer: 0x00000165cdeff6b0>
> pow(tmp5,2)
>
>
>
>
>
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 469.1675
> Min(tmp5)
[1] 53.34385
> mean(tmp5)
[1] 72.23904
> Sum(tmp5)
[1] 14447.81
> Var(tmp5)
[1] 863.0983
>
>
> ## testing functions applied to rows or columns
>
> rowMeans(tmp5)
[1] 89.75939 71.12481 70.70918 70.16214 69.48207 69.89686 68.06184 71.02270
[9] 71.01533 71.15613
> rowSums(tmp5)
[1] 1795.188 1422.496 1414.184 1403.243 1389.641 1397.937 1361.237 1420.454
[9] 1420.307 1423.123
> rowVars(tmp5)
[1] 8020.48079 105.16234 78.36661 48.36296 97.42841 74.79306
[7] 62.95735 77.10367 45.42836 61.79455
> rowSd(tmp5)
[1] 89.557137 10.254869 8.852492 6.954348 9.870583 8.648298 7.934567
[8] 8.780869 6.740057 7.860951
> rowMax(tmp5)
[1] 469.16746 98.71658 90.28108 82.49280 91.19596 85.43600 80.00769
[8] 85.84728 83.17764 80.58235
> rowMin(tmp5)
[1] 58.93950 58.77205 56.60121 58.36031 56.88120 56.45965 54.88822 56.37786
[9] 60.37048 53.34385
>
> colMeans(tmp5)
[1] 113.84169 73.07137 69.06141 69.16649 66.46471 71.81117 70.14584
[8] 68.70929 68.09351 73.28286 69.56936 70.00057 70.89891 70.96945
[15] 70.71168 68.99829 66.72904 68.96966 71.40037 72.88522
> colSums(tmp5)
[1] 1138.4169 730.7137 690.6141 691.6649 664.6471 718.1117 701.4584
[8] 687.0929 680.9351 732.8286 695.6936 700.0057 708.9891 709.6945
[15] 707.1168 689.9829 667.2904 689.6966 714.0037 728.8522
> colVars(tmp5)
[1] 15656.88947 55.73052 48.49523 70.33306 24.31953 99.48365
[7] 43.82410 56.82279 34.79956 48.21128 29.02500 130.71975
[13] 97.97423 49.24264 61.43557 66.65586 62.12393 69.61040
[19] 111.47199 166.66711
> colSd(tmp5)
[1] 125.127493 7.465288 6.963852 8.386481 4.931484 9.974149
[7] 6.619978 7.538089 5.899115 6.943434 5.387485 11.433274
[13] 9.898193 7.017310 7.838084 8.164304 7.881873 8.343285
[19] 10.558029 12.909962
> colMax(tmp5)
[1] 469.16746 82.49280 79.27429 80.03860 74.34421 85.84728 81.28269
[8] 82.63340 74.06327 83.17764 77.54154 90.28108 82.80506 80.58235
[15] 85.61968 80.17824 79.04901 78.37876 91.19596 98.71658
> colMin(tmp5)
[1] 56.88120 62.78425 57.03858 54.88822 59.12243 56.45965 60.63268 60.14733
[9] 55.04302 62.08762 60.66063 53.34385 58.77205 60.55640 59.85238 59.33976
[17] 56.37786 54.04626 56.60121 59.04552
>
>
> ### 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] 89.75939 71.12481 70.70918 NA 69.48207 69.89686 68.06184 71.02270
[9] 71.01533 71.15613
> rowSums(tmp5)
[1] 1795.188 1422.496 1414.184 NA 1389.641 1397.937 1361.237 1420.454
[9] 1420.307 1423.123
> rowVars(tmp5)
[1] 8020.48079 105.16234 78.36661 46.19415 97.42841 74.79306
[7] 62.95735 77.10367 45.42836 61.79455
> rowSd(tmp5)
[1] 89.557137 10.254869 8.852492 6.796628 9.870583 8.648298 7.934567
[8] 8.780869 6.740057 7.860951
> rowMax(tmp5)
[1] 469.16746 98.71658 90.28108 NA 91.19596 85.43600 80.00769
[8] 85.84728 83.17764 80.58235
> rowMin(tmp5)
[1] 58.93950 58.77205 56.60121 NA 56.88120 56.45965 54.88822 56.37786
[9] 60.37048 53.34385
>
> colMeans(tmp5)
[1] 113.84169 73.07137 NA 69.16649 66.46471 71.81117 70.14584
[8] 68.70929 68.09351 73.28286 69.56936 70.00057 70.89891 70.96945
[15] 70.71168 68.99829 66.72904 68.96966 71.40037 72.88522
> colSums(tmp5)
[1] 1138.4169 730.7137 NA 691.6649 664.6471 718.1117 701.4584
[8] 687.0929 680.9351 732.8286 695.6936 700.0057 708.9891 709.6945
[15] 707.1168 689.9829 667.2904 689.6966 714.0037 728.8522
> colVars(tmp5)
[1] 15656.88947 55.73052 NA 70.33306 24.31953 99.48365
[7] 43.82410 56.82279 34.79956 48.21128 29.02500 130.71975
[13] 97.97423 49.24264 61.43557 66.65586 62.12393 69.61040
[19] 111.47199 166.66711
> colSd(tmp5)
[1] 125.127493 7.465288 NA 8.386481 4.931484 9.974149
[7] 6.619978 7.538089 5.899115 6.943434 5.387485 11.433274
[13] 9.898193 7.017310 7.838084 8.164304 7.881873 8.343285
[19] 10.558029 12.909962
> colMax(tmp5)
[1] 469.16746 82.49280 NA 80.03860 74.34421 85.84728 81.28269
[8] 82.63340 74.06327 83.17764 77.54154 90.28108 82.80506 80.58235
[15] 85.61968 80.17824 79.04901 78.37876 91.19596 98.71658
> colMin(tmp5)
[1] 56.88120 62.78425 NA 54.88822 59.12243 56.45965 60.63268 60.14733
[9] 55.04302 62.08762 60.66063 53.34385 58.77205 60.55640 59.85238 59.33976
[17] 56.37786 54.04626 56.60121 59.04552
>
> Max(tmp5,na.rm=TRUE)
[1] 469.1675
> Min(tmp5,na.rm=TRUE)
[1] 53.34385
> mean(tmp5,na.rm=TRUE)
[1] 72.20369
> Sum(tmp5,na.rm=TRUE)
[1] 14368.53
> Var(tmp5,na.rm=TRUE)
[1] 867.2061
>
> rowMeans(tmp5,na.rm=TRUE)
[1] 89.75939 71.12481 70.70918 69.68255 69.48207 69.89686 68.06184 71.02270
[9] 71.01533 71.15613
> rowSums(tmp5,na.rm=TRUE)
[1] 1795.188 1422.496 1414.184 1323.968 1389.641 1397.937 1361.237 1420.454
[9] 1420.307 1423.123
> rowVars(tmp5,na.rm=TRUE)
[1] 8020.48079 105.16234 78.36661 46.19415 97.42841 74.79306
[7] 62.95735 77.10367 45.42836 61.79455
> rowSd(tmp5,na.rm=TRUE)
[1] 89.557137 10.254869 8.852492 6.796628 9.870583 8.648298 7.934567
[8] 8.780869 6.740057 7.860951
> rowMax(tmp5,na.rm=TRUE)
[1] 469.16746 98.71658 90.28108 82.49280 91.19596 85.43600 80.00769
[8] 85.84728 83.17764 80.58235
> rowMin(tmp5,na.rm=TRUE)
[1] 58.93950 58.77205 56.60121 58.36031 56.88120 56.45965 54.88822 56.37786
[9] 60.37048 53.34385
>
> colMeans(tmp5,na.rm=TRUE)
[1] 113.84169 73.07137 67.92665 69.16649 66.46471 71.81117 70.14584
[8] 68.70929 68.09351 73.28286 69.56936 70.00057 70.89891 70.96945
[15] 70.71168 68.99829 66.72904 68.96966 71.40037 72.88522
> colSums(tmp5,na.rm=TRUE)
[1] 1138.4169 730.7137 611.3398 691.6649 664.6471 718.1117 701.4584
[8] 687.0929 680.9351 732.8286 695.6936 700.0057 708.9891 709.6945
[15] 707.1168 689.9829 667.2904 689.6966 714.0037 728.8522
> colVars(tmp5,na.rm=TRUE)
[1] 15656.88947 55.73052 40.07063 70.33306 24.31953 99.48365
[7] 43.82410 56.82279 34.79956 48.21128 29.02500 130.71975
[13] 97.97423 49.24264 61.43557 66.65586 62.12393 69.61040
[19] 111.47199 166.66711
> colSd(tmp5,na.rm=TRUE)
[1] 125.127493 7.465288 6.330136 8.386481 4.931484 9.974149
[7] 6.619978 7.538089 5.899115 6.943434 5.387485 11.433274
[13] 9.898193 7.017310 7.838084 8.164304 7.881873 8.343285
[19] 10.558029 12.909962
> colMax(tmp5,na.rm=TRUE)
[1] 469.16746 82.49280 75.52707 80.03860 74.34421 85.84728 81.28269
[8] 82.63340 74.06327 83.17764 77.54154 90.28108 82.80506 80.58235
[15] 85.61968 80.17824 79.04901 78.37876 91.19596 98.71658
> colMin(tmp5,na.rm=TRUE)
[1] 56.88120 62.78425 57.03858 54.88822 59.12243 56.45965 60.63268 60.14733
[9] 55.04302 62.08762 60.66063 53.34385 58.77205 60.55640 59.85238 59.33976
[17] 56.37786 54.04626 56.60121 59.04552
>
> # now set an entire row to NA
>
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
[1] 89.75939 71.12481 70.70918 NaN 69.48207 69.89686 68.06184 71.02270
[9] 71.01533 71.15613
> rowSums(tmp5,na.rm=TRUE)
[1] 1795.188 1422.496 1414.184 0.000 1389.641 1397.937 1361.237 1420.454
[9] 1420.307 1423.123
> rowVars(tmp5,na.rm=TRUE)
[1] 8020.48079 105.16234 78.36661 NA 97.42841 74.79306
[7] 62.95735 77.10367 45.42836 61.79455
> rowSd(tmp5,na.rm=TRUE)
[1] 89.557137 10.254869 8.852492 NA 9.870583 8.648298 7.934567
[8] 8.780869 6.740057 7.860951
> rowMax(tmp5,na.rm=TRUE)
[1] 469.16746 98.71658 90.28108 NA 91.19596 85.43600 80.00769
[8] 85.84728 83.17764 80.58235
> rowMin(tmp5,na.rm=TRUE)
[1] 58.93950 58.77205 56.60121 NA 56.88120 56.45965 54.88822 56.37786
[9] 60.37048 53.34385
>
>
> # now set an entire col to NA
>
>
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
[1] 118.79607 72.02455 NaN 69.76436 66.94348 72.67481 70.51966
[8] 68.88769 68.21823 73.82713 69.14221 71.29393 70.44410 70.47769
[15] 70.87021 67.85678 67.22350 67.92421 70.71294 73.86806
> colSums(tmp5,na.rm=TRUE)
[1] 1069.1646 648.2209 0.0000 627.8793 602.4913 654.0733 634.6769
[8] 619.9892 613.9641 664.4441 622.2799 641.6453 633.9969 634.2992
[15] 637.8319 610.7110 605.0115 611.3178 636.4164 664.8126
> colVars(tmp5,na.rm=TRUE)
[1] 17337.85929 50.36861 NA 75.10334 24.78073 103.52807
[7] 47.73004 63.56758 38.97452 50.90508 30.60041 128.24091
[13] 107.89393 52.67747 68.83225 60.32853 67.13898 66.01570
[19] 120.08955 176.63328
> colSd(tmp5,na.rm=TRUE)
[1] 131.673305 7.097085 NA 8.666219 4.978025 10.174875
[7] 6.908693 7.972928 6.242957 7.134780 5.531764 11.324350
[13] 10.387200 7.257924 8.296520 7.767144 8.193838 8.125005
[19] 10.958538 13.290345
> colMax(tmp5,na.rm=TRUE)
[1] 469.16746 80.57345 -Inf 80.03860 74.34421 85.84728 81.28269
[8] 82.63340 74.06327 83.17764 77.54154 90.28108 82.80506 80.58235
[15] 85.61968 80.17824 79.04901 77.04484 91.19596 98.71658
> colMin(tmp5,na.rm=TRUE)
[1] 56.88120 62.78425 Inf 54.88822 59.12243 56.45965 60.63268 60.14733
[9] 55.04302 62.08762 60.66063 53.34385 58.77205 60.55640 59.85238 59.33976
[17] 56.37786 54.04626 56.60121 59.04552
>
>
>
>
> 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] 142.7962 279.0861 172.2666 119.9430 356.8508 185.5924 229.4717 283.3680
[9] 272.9185 246.5640
> apply(copymatrix,1,var,na.rm=TRUE)
[1] 142.7962 279.0861 172.2666 119.9430 356.8508 185.5924 229.4717 283.3680
[9] 272.9185 246.5640
>
>
>
> 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 -1.421085e-14 8.526513e-14 -1.421085e-13 0.000000e+00
[6] 1.705303e-13 -4.263256e-14 -7.105427e-14 1.136868e-13 8.526513e-14
[11] -1.421085e-14 -1.136868e-13 1.278977e-13 -4.263256e-14 1.705303e-13
[16] 2.842171e-14 1.136868e-13 0.000000e+00 0.000000e+00 -2.842171e-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)
+ }
8 5
1 5
4 9
3 19
7 15
9 14
9 16
4 12
10 11
5 11
5 8
7 18
10 20
6 8
4 6
7 20
2 18
10 12
6 20
1 14
There were 50 or more warnings (use warnings() to see the first 50)
>
>
> ### now test 1 by n and n by 1 matrix
>
>
> err.tol <- 1e-12
>
> rm(tmp5)
>
> dataset1 <- rnorm(100)
> dataset2 <- rnorm(100)
>
> tmp <- createBufferedMatrix(1,100)
> tmp[1,] <- dataset1
>
> tmp2 <- createBufferedMatrix(100,1)
> tmp2[,1] <- dataset2
>
>
>
>
>
> Max(tmp)
[1] 2.415477
> Min(tmp)
[1] -2.611223
> mean(tmp)
[1] -0.1301286
> Sum(tmp)
[1] -13.01286
> Var(tmp)
[1] 1.051415
>
> rowMeans(tmp)
[1] -0.1301286
> rowSums(tmp)
[1] -13.01286
> rowVars(tmp)
[1] 1.051415
> rowSd(tmp)
[1] 1.025385
> rowMax(tmp)
[1] 2.415477
> rowMin(tmp)
[1] -2.611223
>
> colMeans(tmp)
[1] -1.37942498 -0.04996978 1.06639312 0.12039988 -0.15513551 0.75605789
[7] 0.50226488 0.05717247 0.67854872 0.43824272 -0.63685737 -0.88024391
[13] -1.53527165 -0.67633496 -0.56011646 1.89777169 1.00322620 -0.71224557
[19] -1.58781933 -1.65316625 0.38277667 2.29274571 -0.30772730 -0.18845251
[25] 0.85036323 0.43841088 0.62428878 -0.63340830 1.64565738 -1.04982114
[31] -1.37292869 -0.78427636 -0.03226466 -0.95863765 0.60664233 -1.39022887
[37] -0.36601588 -0.07655406 0.79493200 -0.69217262 -0.05422838 -0.62973239
[43] -0.17945679 -1.27935166 -0.58030291 -1.00772141 2.16567442 -0.68293421
[49] 2.41547746 -0.96657894 0.06642373 -0.66981502 -2.61122293 -1.73225260
[55] -0.81685690 0.13638246 -0.42081764 1.16344494 -1.45445335 -0.05006732
[61] 1.18246300 0.12970040 0.55368918 -0.96866173 1.23803436 -0.14674758
[67] 0.12696785 -0.22865714 0.33046524 -1.49206813 -0.16611764 0.31780719
[73] -0.99778407 1.67845891 -1.43599562 -0.15983477 -0.14346266 -1.15964421
[79] 0.24567698 -1.86978467 -0.60375634 -0.44163918 2.20843358 -1.07072923
[85] 0.29138137 0.85100102 -0.27037331 0.13730496 -0.15953719 0.74282969
[91] 1.23146058 0.02763634 -0.99792064 -0.48982877 -0.01113749 1.16778673
[97] -0.77309586 -1.23205460 1.85929998 -1.80285317
> colSums(tmp)
[1] -1.37942498 -0.04996978 1.06639312 0.12039988 -0.15513551 0.75605789
[7] 0.50226488 0.05717247 0.67854872 0.43824272 -0.63685737 -0.88024391
[13] -1.53527165 -0.67633496 -0.56011646 1.89777169 1.00322620 -0.71224557
[19] -1.58781933 -1.65316625 0.38277667 2.29274571 -0.30772730 -0.18845251
[25] 0.85036323 0.43841088 0.62428878 -0.63340830 1.64565738 -1.04982114
[31] -1.37292869 -0.78427636 -0.03226466 -0.95863765 0.60664233 -1.39022887
[37] -0.36601588 -0.07655406 0.79493200 -0.69217262 -0.05422838 -0.62973239
[43] -0.17945679 -1.27935166 -0.58030291 -1.00772141 2.16567442 -0.68293421
[49] 2.41547746 -0.96657894 0.06642373 -0.66981502 -2.61122293 -1.73225260
[55] -0.81685690 0.13638246 -0.42081764 1.16344494 -1.45445335 -0.05006732
[61] 1.18246300 0.12970040 0.55368918 -0.96866173 1.23803436 -0.14674758
[67] 0.12696785 -0.22865714 0.33046524 -1.49206813 -0.16611764 0.31780719
[73] -0.99778407 1.67845891 -1.43599562 -0.15983477 -0.14346266 -1.15964421
[79] 0.24567698 -1.86978467 -0.60375634 -0.44163918 2.20843358 -1.07072923
[85] 0.29138137 0.85100102 -0.27037331 0.13730496 -0.15953719 0.74282969
[91] 1.23146058 0.02763634 -0.99792064 -0.48982877 -0.01113749 1.16778673
[97] -0.77309586 -1.23205460 1.85929998 -1.80285317
> colVars(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colSd(tmp)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colMax(tmp)
[1] -1.37942498 -0.04996978 1.06639312 0.12039988 -0.15513551 0.75605789
[7] 0.50226488 0.05717247 0.67854872 0.43824272 -0.63685737 -0.88024391
[13] -1.53527165 -0.67633496 -0.56011646 1.89777169 1.00322620 -0.71224557
[19] -1.58781933 -1.65316625 0.38277667 2.29274571 -0.30772730 -0.18845251
[25] 0.85036323 0.43841088 0.62428878 -0.63340830 1.64565738 -1.04982114
[31] -1.37292869 -0.78427636 -0.03226466 -0.95863765 0.60664233 -1.39022887
[37] -0.36601588 -0.07655406 0.79493200 -0.69217262 -0.05422838 -0.62973239
[43] -0.17945679 -1.27935166 -0.58030291 -1.00772141 2.16567442 -0.68293421
[49] 2.41547746 -0.96657894 0.06642373 -0.66981502 -2.61122293 -1.73225260
[55] -0.81685690 0.13638246 -0.42081764 1.16344494 -1.45445335 -0.05006732
[61] 1.18246300 0.12970040 0.55368918 -0.96866173 1.23803436 -0.14674758
[67] 0.12696785 -0.22865714 0.33046524 -1.49206813 -0.16611764 0.31780719
[73] -0.99778407 1.67845891 -1.43599562 -0.15983477 -0.14346266 -1.15964421
[79] 0.24567698 -1.86978467 -0.60375634 -0.44163918 2.20843358 -1.07072923
[85] 0.29138137 0.85100102 -0.27037331 0.13730496 -0.15953719 0.74282969
[91] 1.23146058 0.02763634 -0.99792064 -0.48982877 -0.01113749 1.16778673
[97] -0.77309586 -1.23205460 1.85929998 -1.80285317
> colMin(tmp)
[1] -1.37942498 -0.04996978 1.06639312 0.12039988 -0.15513551 0.75605789
[7] 0.50226488 0.05717247 0.67854872 0.43824272 -0.63685737 -0.88024391
[13] -1.53527165 -0.67633496 -0.56011646 1.89777169 1.00322620 -0.71224557
[19] -1.58781933 -1.65316625 0.38277667 2.29274571 -0.30772730 -0.18845251
[25] 0.85036323 0.43841088 0.62428878 -0.63340830 1.64565738 -1.04982114
[31] -1.37292869 -0.78427636 -0.03226466 -0.95863765 0.60664233 -1.39022887
[37] -0.36601588 -0.07655406 0.79493200 -0.69217262 -0.05422838 -0.62973239
[43] -0.17945679 -1.27935166 -0.58030291 -1.00772141 2.16567442 -0.68293421
[49] 2.41547746 -0.96657894 0.06642373 -0.66981502 -2.61122293 -1.73225260
[55] -0.81685690 0.13638246 -0.42081764 1.16344494 -1.45445335 -0.05006732
[61] 1.18246300 0.12970040 0.55368918 -0.96866173 1.23803436 -0.14674758
[67] 0.12696785 -0.22865714 0.33046524 -1.49206813 -0.16611764 0.31780719
[73] -0.99778407 1.67845891 -1.43599562 -0.15983477 -0.14346266 -1.15964421
[79] 0.24567698 -1.86978467 -0.60375634 -0.44163918 2.20843358 -1.07072923
[85] 0.29138137 0.85100102 -0.27037331 0.13730496 -0.15953719 0.74282969
[91] 1.23146058 0.02763634 -0.99792064 -0.48982877 -0.01113749 1.16778673
[97] -0.77309586 -1.23205460 1.85929998 -1.80285317
> colMedians(tmp)
[1] -1.37942498 -0.04996978 1.06639312 0.12039988 -0.15513551 0.75605789
[7] 0.50226488 0.05717247 0.67854872 0.43824272 -0.63685737 -0.88024391
[13] -1.53527165 -0.67633496 -0.56011646 1.89777169 1.00322620 -0.71224557
[19] -1.58781933 -1.65316625 0.38277667 2.29274571 -0.30772730 -0.18845251
[25] 0.85036323 0.43841088 0.62428878 -0.63340830 1.64565738 -1.04982114
[31] -1.37292869 -0.78427636 -0.03226466 -0.95863765 0.60664233 -1.39022887
[37] -0.36601588 -0.07655406 0.79493200 -0.69217262 -0.05422838 -0.62973239
[43] -0.17945679 -1.27935166 -0.58030291 -1.00772141 2.16567442 -0.68293421
[49] 2.41547746 -0.96657894 0.06642373 -0.66981502 -2.61122293 -1.73225260
[55] -0.81685690 0.13638246 -0.42081764 1.16344494 -1.45445335 -0.05006732
[61] 1.18246300 0.12970040 0.55368918 -0.96866173 1.23803436 -0.14674758
[67] 0.12696785 -0.22865714 0.33046524 -1.49206813 -0.16611764 0.31780719
[73] -0.99778407 1.67845891 -1.43599562 -0.15983477 -0.14346266 -1.15964421
[79] 0.24567698 -1.86978467 -0.60375634 -0.44163918 2.20843358 -1.07072923
[85] 0.29138137 0.85100102 -0.27037331 0.13730496 -0.15953719 0.74282969
[91] 1.23146058 0.02763634 -0.99792064 -0.48982877 -0.01113749 1.16778673
[97] -0.77309586 -1.23205460 1.85929998 -1.80285317
> colRanges(tmp)
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] -1.379425 -0.04996978 1.066393 0.1203999 -0.1551355 0.7560579 0.5022649
[2,] -1.379425 -0.04996978 1.066393 0.1203999 -0.1551355 0.7560579 0.5022649
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
[1,] 0.05717247 0.6785487 0.4382427 -0.6368574 -0.8802439 -1.535272 -0.676335
[2,] 0.05717247 0.6785487 0.4382427 -0.6368574 -0.8802439 -1.535272 -0.676335
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] -0.5601165 1.897772 1.003226 -0.7122456 -1.587819 -1.653166 0.3827767
[2,] -0.5601165 1.897772 1.003226 -0.7122456 -1.587819 -1.653166 0.3827767
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
[1,] 2.292746 -0.3077273 -0.1884525 0.8503632 0.4384109 0.6242888 -0.6334083
[2,] 2.292746 -0.3077273 -0.1884525 0.8503632 0.4384109 0.6242888 -0.6334083
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
[1,] 1.645657 -1.049821 -1.372929 -0.7842764 -0.03226466 -0.9586376 0.6066423
[2,] 1.645657 -1.049821 -1.372929 -0.7842764 -0.03226466 -0.9586376 0.6066423
[,36] [,37] [,38] [,39] [,40] [,41]
[1,] -1.390229 -0.3660159 -0.07655406 0.794932 -0.6921726 -0.05422838
[2,] -1.390229 -0.3660159 -0.07655406 0.794932 -0.6921726 -0.05422838
[,42] [,43] [,44] [,45] [,46] [,47] [,48]
[1,] -0.6297324 -0.1794568 -1.279352 -0.5803029 -1.007721 2.165674 -0.6829342
[2,] -0.6297324 -0.1794568 -1.279352 -0.5803029 -1.007721 2.165674 -0.6829342
[,49] [,50] [,51] [,52] [,53] [,54] [,55]
[1,] 2.415477 -0.9665789 0.06642373 -0.669815 -2.611223 -1.732253 -0.8168569
[2,] 2.415477 -0.9665789 0.06642373 -0.669815 -2.611223 -1.732253 -0.8168569
[,56] [,57] [,58] [,59] [,60] [,61] [,62]
[1,] 0.1363825 -0.4208176 1.163445 -1.454453 -0.05006732 1.182463 0.1297004
[2,] 0.1363825 -0.4208176 1.163445 -1.454453 -0.05006732 1.182463 0.1297004
[,63] [,64] [,65] [,66] [,67] [,68] [,69]
[1,] 0.5536892 -0.9686617 1.238034 -0.1467476 0.1269679 -0.2286571 0.3304652
[2,] 0.5536892 -0.9686617 1.238034 -0.1467476 0.1269679 -0.2286571 0.3304652
[,70] [,71] [,72] [,73] [,74] [,75] [,76]
[1,] -1.492068 -0.1661176 0.3178072 -0.9977841 1.678459 -1.435996 -0.1598348
[2,] -1.492068 -0.1661176 0.3178072 -0.9977841 1.678459 -1.435996 -0.1598348
[,77] [,78] [,79] [,80] [,81] [,82] [,83]
[1,] -0.1434627 -1.159644 0.245677 -1.869785 -0.6037563 -0.4416392 2.208434
[2,] -0.1434627 -1.159644 0.245677 -1.869785 -0.6037563 -0.4416392 2.208434
[,84] [,85] [,86] [,87] [,88] [,89] [,90]
[1,] -1.070729 0.2913814 0.851001 -0.2703733 0.137305 -0.1595372 0.7428297
[2,] -1.070729 0.2913814 0.851001 -0.2703733 0.137305 -0.1595372 0.7428297
[,91] [,92] [,93] [,94] [,95] [,96] [,97]
[1,] 1.231461 0.02763634 -0.9979206 -0.4898288 -0.01113749 1.167787 -0.7730959
[2,] 1.231461 0.02763634 -0.9979206 -0.4898288 -0.01113749 1.167787 -0.7730959
[,98] [,99] [,100]
[1,] -1.232055 1.8593 -1.802853
[2,] -1.232055 1.8593 -1.802853
>
>
> Max(tmp2)
[1] 1.980888
> Min(tmp2)
[1] -2.590191
> mean(tmp2)
[1] 0.05404
> Sum(tmp2)
[1] 5.404
> Var(tmp2)
[1] 0.8073663
>
> rowMeans(tmp2)
[1] -0.01605422 -0.90173308 0.48928099 0.25408435 0.41533833 0.69267493
[7] -0.36964210 1.06544084 0.53080213 -1.33203523 0.61882401 0.51319089
[13] 0.47551181 -1.31154250 1.30467576 -0.84640494 -0.92432580 -2.33840333
[19] 0.38176178 -0.98902548 -1.13626069 1.22932397 0.48367163 0.32000190
[25] 1.18847117 -0.04219295 -2.59019131 -1.09880394 0.50325223 0.19795878
[31] -0.04687016 0.84469989 1.41165407 1.03439524 -0.83518718 0.17205862
[37] -0.01344979 -0.96277722 0.93868628 -0.93903543 1.05703487 -0.29298907
[43] 0.59095029 0.61971564 -0.37171112 -0.42425826 0.76674365 -0.01290810
[49] 1.59298479 0.76408228 -0.88164879 0.08577449 0.44737774 0.72079633
[55] -0.53685502 -0.31451319 -1.16052356 1.01053143 -0.36507351 -1.53038341
[61] -0.03976565 0.42052678 0.73834249 0.74005867 0.83071962 0.11980125
[67] -1.48404208 0.25639810 -0.06446679 1.26743488 -0.69878595 -0.29259665
[73] 0.73504897 1.98088835 -0.44016152 -0.21021053 1.37050651 -1.06163690
[79] -0.44227774 0.45924042 -0.31029334 -0.26674534 0.71684868 -0.15079972
[85] 1.59201470 -0.40828158 -0.50538399 -0.89887601 1.13258125 -0.31356557
[91] -0.55015892 1.77232052 -1.64640288 0.61233294 -1.07451360 0.66864157
[97] -0.56317883 0.18116408 0.02849639 1.06582570
> rowSums(tmp2)
[1] -0.01605422 -0.90173308 0.48928099 0.25408435 0.41533833 0.69267493
[7] -0.36964210 1.06544084 0.53080213 -1.33203523 0.61882401 0.51319089
[13] 0.47551181 -1.31154250 1.30467576 -0.84640494 -0.92432580 -2.33840333
[19] 0.38176178 -0.98902548 -1.13626069 1.22932397 0.48367163 0.32000190
[25] 1.18847117 -0.04219295 -2.59019131 -1.09880394 0.50325223 0.19795878
[31] -0.04687016 0.84469989 1.41165407 1.03439524 -0.83518718 0.17205862
[37] -0.01344979 -0.96277722 0.93868628 -0.93903543 1.05703487 -0.29298907
[43] 0.59095029 0.61971564 -0.37171112 -0.42425826 0.76674365 -0.01290810
[49] 1.59298479 0.76408228 -0.88164879 0.08577449 0.44737774 0.72079633
[55] -0.53685502 -0.31451319 -1.16052356 1.01053143 -0.36507351 -1.53038341
[61] -0.03976565 0.42052678 0.73834249 0.74005867 0.83071962 0.11980125
[67] -1.48404208 0.25639810 -0.06446679 1.26743488 -0.69878595 -0.29259665
[73] 0.73504897 1.98088835 -0.44016152 -0.21021053 1.37050651 -1.06163690
[79] -0.44227774 0.45924042 -0.31029334 -0.26674534 0.71684868 -0.15079972
[85] 1.59201470 -0.40828158 -0.50538399 -0.89887601 1.13258125 -0.31356557
[91] -0.55015892 1.77232052 -1.64640288 0.61233294 -1.07451360 0.66864157
[97] -0.56317883 0.18116408 0.02849639 1.06582570
> rowVars(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowSd(tmp2)
[1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
[76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowMax(tmp2)
[1] -0.01605422 -0.90173308 0.48928099 0.25408435 0.41533833 0.69267493
[7] -0.36964210 1.06544084 0.53080213 -1.33203523 0.61882401 0.51319089
[13] 0.47551181 -1.31154250 1.30467576 -0.84640494 -0.92432580 -2.33840333
[19] 0.38176178 -0.98902548 -1.13626069 1.22932397 0.48367163 0.32000190
[25] 1.18847117 -0.04219295 -2.59019131 -1.09880394 0.50325223 0.19795878
[31] -0.04687016 0.84469989 1.41165407 1.03439524 -0.83518718 0.17205862
[37] -0.01344979 -0.96277722 0.93868628 -0.93903543 1.05703487 -0.29298907
[43] 0.59095029 0.61971564 -0.37171112 -0.42425826 0.76674365 -0.01290810
[49] 1.59298479 0.76408228 -0.88164879 0.08577449 0.44737774 0.72079633
[55] -0.53685502 -0.31451319 -1.16052356 1.01053143 -0.36507351 -1.53038341
[61] -0.03976565 0.42052678 0.73834249 0.74005867 0.83071962 0.11980125
[67] -1.48404208 0.25639810 -0.06446679 1.26743488 -0.69878595 -0.29259665
[73] 0.73504897 1.98088835 -0.44016152 -0.21021053 1.37050651 -1.06163690
[79] -0.44227774 0.45924042 -0.31029334 -0.26674534 0.71684868 -0.15079972
[85] 1.59201470 -0.40828158 -0.50538399 -0.89887601 1.13258125 -0.31356557
[91] -0.55015892 1.77232052 -1.64640288 0.61233294 -1.07451360 0.66864157
[97] -0.56317883 0.18116408 0.02849639 1.06582570
> rowMin(tmp2)
[1] -0.01605422 -0.90173308 0.48928099 0.25408435 0.41533833 0.69267493
[7] -0.36964210 1.06544084 0.53080213 -1.33203523 0.61882401 0.51319089
[13] 0.47551181 -1.31154250 1.30467576 -0.84640494 -0.92432580 -2.33840333
[19] 0.38176178 -0.98902548 -1.13626069 1.22932397 0.48367163 0.32000190
[25] 1.18847117 -0.04219295 -2.59019131 -1.09880394 0.50325223 0.19795878
[31] -0.04687016 0.84469989 1.41165407 1.03439524 -0.83518718 0.17205862
[37] -0.01344979 -0.96277722 0.93868628 -0.93903543 1.05703487 -0.29298907
[43] 0.59095029 0.61971564 -0.37171112 -0.42425826 0.76674365 -0.01290810
[49] 1.59298479 0.76408228 -0.88164879 0.08577449 0.44737774 0.72079633
[55] -0.53685502 -0.31451319 -1.16052356 1.01053143 -0.36507351 -1.53038341
[61] -0.03976565 0.42052678 0.73834249 0.74005867 0.83071962 0.11980125
[67] -1.48404208 0.25639810 -0.06446679 1.26743488 -0.69878595 -0.29259665
[73] 0.73504897 1.98088835 -0.44016152 -0.21021053 1.37050651 -1.06163690
[79] -0.44227774 0.45924042 -0.31029334 -0.26674534 0.71684868 -0.15079972
[85] 1.59201470 -0.40828158 -0.50538399 -0.89887601 1.13258125 -0.31356557
[91] -0.55015892 1.77232052 -1.64640288 0.61233294 -1.07451360 0.66864157
[97] -0.56317883 0.18116408 0.02849639 1.06582570
>
> colMeans(tmp2)
[1] 0.05404
> colSums(tmp2)
[1] 5.404
> colVars(tmp2)
[1] 0.8073663
> colSd(tmp2)
[1] 0.8985357
> colMax(tmp2)
[1] 1.980888
> colMin(tmp2)
[1] -2.590191
> colMedians(tmp2)
[1] 0.1027879
> colRanges(tmp2)
[,1]
[1,] -2.590191
[2,] 1.980888
>
> 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] -2.636551 -1.594505 1.042234 -0.641748 -2.736314 -2.269830 2.294908
[8] -5.019328 -0.262950 6.312247
> colApply(tmp,quantile)[,1]
[,1]
[1,] -1.33852799
[2,] -0.49904522
[3,] -0.08616287
[4,] 0.07541835
[5,] 0.44989754
>
> rowApply(tmp,sum)
[1] 0.8647655 0.5317161 1.5810406 -3.6916320 1.9480802 -1.0147964
[7] 0.4220028 -1.8625277 -1.2504680 -3.0400182
> rowApply(tmp,rank)[1:10,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 8 7 6 6 4 3 6 2 2 7
[2,] 9 1 10 3 8 1 4 9 1 8
[3,] 3 8 3 2 10 5 10 8 4 1
[4,] 1 10 2 8 9 8 1 5 5 4
[5,] 6 5 7 7 1 4 8 4 3 6
[6,] 2 9 5 1 3 7 3 7 10 3
[7,] 5 2 1 9 7 9 5 10 8 10
[8,] 4 3 4 4 5 2 2 1 9 9
[9,] 7 6 8 5 2 6 9 3 6 2
[10,] 10 4 9 10 6 10 7 6 7 5
>
> tmp <- createBufferedMatrix(5,20)
>
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
[1] 7.45352060 1.79966651 -1.22816295 -3.56929649 1.73715434 1.60324300
[7] -1.89172375 -2.93257663 2.81975846 3.11698955 -0.66373363 2.45622697
[13] 0.15257716 0.46160388 -0.57268553 2.22141144 0.04466835 -0.38012036
[19] 1.25239520 0.39899537
> colApply(tmp,quantile)[,1]
[,1]
[1,] 0.7440107
[2,] 0.7447726
[3,] 1.4401054
[4,] 1.4510179
[5,] 3.0736140
>
> rowApply(tmp,sum)
[1] 4.614225 0.745951 8.885568 1.663277 -1.629109
> rowApply(tmp,rank)[1:5,]
[,1] [,2] [,3] [,4] [,5]
[1,] 20 18 20 15 19
[2,] 14 2 15 3 20
[3,] 6 11 2 6 17
[4,] 3 7 4 1 16
[5,] 13 13 12 16 6
>
>
> as.matrix(tmp)
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 1.4401054 0.7627322 -0.3712505 -1.0321934 0.7391669 1.1016203
[2,] 0.7447726 -0.8521202 0.1105176 -0.2208850 0.2638170 0.5591680
[3,] 3.0736140 1.1797812 -0.9933538 -0.7529777 0.6573298 0.4487382
[4,] 0.7440107 -0.9653105 -0.7274765 -2.0000667 0.9263139 0.6207671
[5,] 1.4510179 1.6745837 0.7534002 0.4368264 -0.8494732 -1.1270506
[,7] [,8] [,9] [,10] [,11] [,12]
[1,] -0.4768720 -1.4209738 -0.6690931 -0.008718315 0.40001711 1.33920107
[2,] -0.2569122 -0.9767248 0.5805382 0.144140345 -0.65099360 -0.14699864
[3,] 0.5605671 0.4789785 0.1454575 1.380565163 0.84362766 0.97572995
[4,] -0.7504536 -0.6926489 1.5809976 1.484921547 -0.02071443 0.05054942
[5,] -0.9680530 -0.3212077 1.1818582 0.116080812 -1.23567036 0.23774518
[,13] [,14] [,15] [,16] [,17] [,18]
[1,] -1.17128895 0.79727675 0.2996038 0.4714391 1.0667759 0.20996983
[2,] 0.06133708 0.38151973 -0.8145094 0.4260469 -0.4827647 0.98995839
[3,] -0.51695629 0.27683509 1.4530111 1.2188736 -1.1771759 -0.73010205
[4,] 1.66023193 -0.02100243 -1.0353110 0.5528160 1.3247127 0.06438208
[5,] 0.11925340 -0.97302526 -0.4754801 -0.4477642 -0.6868797 -0.91432860
[,19] [,20]
[1,] 1.2617606 -0.1250543
[2,] 0.7838596 0.1021842
[3,] -0.9454101 1.3084345
[4,] -0.1978927 -0.9355493
[5,] 0.3500778 0.0489803
>
>
> is.BufferedMatrix(tmp)
[1] TRUE
>
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size: 5 20
Buffer size: 1 1
Directory: F:/biocbuild/bbs-3.20-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-3.20-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-3.20-bioc/meat/BufferedMatrix.Rcheck/tests
Prefix: BM
Mode: Col mode
Read Only: FALSE
Memory usage : 545 bytes.
Disk usage : 160 bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size: 3 20
Buffer size: 1 1
Directory: F:/biocbuild/bbs-3.20-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 1.08914 0.8163575 0.424424 -1.410219 0.6841998 -1.806433 1.217479
col8 col9 col10 col11 col12 col13 col14
row1 0.1556712 -0.6194718 0.898636 -0.3121604 0.1156885 0.1021986 -0.9099012
col15 col16 col17 col18 col19 col20
row1 -0.9415544 -0.7020483 0.7114559 -0.7497748 1.475884 1.021674
> tmp[,"col10"]
col10
row1 0.8986360
row2 2.3925094
row3 -0.9472241
row4 -0.6009762
row5 -0.2363932
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7
row1 1.089140 0.8163575 0.424424 -1.410219 0.68419985 -1.8064327 1.217479
row5 -1.607931 -1.4378134 -1.501387 0.950917 -0.01306025 0.6056944 -0.707213
col8 col9 col10 col11 col12 col13
row1 0.1556712 -0.6194718 0.8986360 -0.31216038 0.1156885 0.1021986
row5 -0.9312095 1.4904559 -0.2363932 -0.02731519 -0.2323611 -0.3557288
col14 col15 col16 col17 col18 col19
row1 -0.9099012 -0.9415544 -0.7020483 0.7114559 -0.7497748 1.4758844
row5 -1.9054244 -1.1312127 -0.9186877 0.7871191 0.4312378 -0.8600665
col20
row1 1.02167443
row5 -0.06560455
> tmp[,c("col6","col20")]
col6 col20
row1 -1.8064327 1.02167443
row2 1.0701900 0.81490780
row3 0.4870237 1.91539015
row4 0.7368208 -0.91194992
row5 0.6056944 -0.06560455
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 -1.8064327 1.02167443
row5 0.6056944 -0.06560455
>
>
>
>
> 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 51.16737 50.96955 52.04141 49.47387 49.83146 105.9666 48.75871 51.36124
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.5713 49.2078 50.14719 50.62559 51.14958 48.80569 50.43984 49.51198
col17 col18 col19 col20
row1 48.55478 50.34598 49.04943 104.4975
> tmp[,"col10"]
col10
row1 49.20780
row2 30.76829
row3 31.56703
row4 28.92165
row5 49.82470
> tmp[c("row1","row5"),]
col1 col2 col3 col4 col5 col6 col7 col8
row1 51.16737 50.96955 52.04141 49.47387 49.83146 105.9666 48.75871 51.36124
row5 51.26883 49.92264 49.33080 50.97475 48.95976 104.4751 50.91069 49.15852
col9 col10 col11 col12 col13 col14 col15 col16
row1 49.57130 49.2078 50.14719 50.62559 51.14958 48.80569 50.43984 49.51198
row5 49.59144 49.8247 50.73446 50.57916 50.07280 51.03793 50.34135 49.29535
col17 col18 col19 col20
row1 48.55478 50.34598 49.04943 104.4975
row5 50.20079 50.94039 49.05035 104.8642
> tmp[,c("col6","col20")]
col6 col20
row1 105.96657 104.49751
row2 75.34104 75.26262
row3 76.90406 75.49323
row4 74.14481 75.73179
row5 104.47515 104.86417
> tmp[c("row1","row5"),c("col6","col20")]
col6 col20
row1 105.9666 104.4975
row5 104.4751 104.8642
>
>
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
col6 col20
row1 105.9666 104.4975
row5 104.4751 104.8642
>
>
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
>
> tmp[,"col13"]
col13
[1,] 0.8853468
[2,] -1.0198364
[3,] 0.0122590
[4,] -1.3911035
[5,] -0.4083190
> tmp[,c("col17","col7")]
col17 col7
[1,] -0.9428814 -0.44801876
[2,] 0.2598380 0.24824635
[3,] -1.4954198 -0.24210243
[4,] -0.3288581 -0.09135052
[5,] 1.4883913 -0.50130108
>
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
col6 col20
[1,] -1.3871861 -1.0256896
[2,] 0.6821950 0.5872991
[3,] 0.7606886 -0.1852059
[4,] -0.3986684 -1.4261836
[5,] -1.3221924 -1.7239057
> subBufferedMatrix(tmp,1,c("col6"))[,1]
col1
[1,] -1.387186
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
col6
[1,] -1.387186
[2,] 0.682195
>
>
>
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
>
>
>
>
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row3 1.0614067 0.40265916 -0.0565156 -2.209623 -0.3170172 0.06926083 1.118966
row1 0.2537382 0.07020148 -1.1226004 1.257691 -1.8295290 0.23739616 2.682400
[,8] [,9] [,10] [,11] [,12] [,13]
row3 0.7622414 1.21899967 0.4054358 -0.3152710 1.4796378 0.3895622
row1 -0.1805293 -0.05478815 -0.1936880 0.9312105 -0.1431108 1.0505348
[,14] [,15] [,16] [,17] [,18] [,19] [,20]
row3 0.4091478 -0.5779791 1.212869 1.4333041 1.3469983 -0.5346701 2.0142506
row1 0.3635379 -0.5519007 1.003649 -0.7781854 0.2302923 -1.6332642 -0.2468273
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row2 -0.3206689 -0.7418561 0.5735365 0.9986627 -0.3516869 1.809125 -0.668289
[,8] [,9] [,10]
row2 0.7537436 -1.483081 0.04094977
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
row5 0.9539458 -0.2955144 -1.197465 1.04139 -0.9435775 -0.09617776 0.5041926
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
row5 -0.4084017 -0.465893 0.3101879 1.581278 0.2611458 -0.2831311 -0.3976889
[,15] [,16] [,17] [,18] [,19] [,20]
row5 -0.2064482 0.7386692 0.7547232 1.092594 -1.005721 1.452392
>
>
> 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: 0x00000165cdeff7d0>
> is.ReadOnlyMode(tmp)
[1] TRUE
>
> filenames(tmp)
[1] "F:/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests\\BM20a2069b07c03"
[2] "F:/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests\\BM20a20476929c8"
[3] "F:/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests\\BM20a2011e55514"
[4] "F:/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests\\BM20a205d64418e"
[5] "F:/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests\\BM20a205b36f87"
[6] "F:/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests\\BM20a2036b21cec"
[7] "F:/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests\\BM20a2019fb2aca"
[8] "F:/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests\\BM20a205ad873eb"
[9] "F:/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests\\BM20a207af1454e"
[10] "F:/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests\\BM20a205566f95"
[11] "F:/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests\\BM20a205ac66096"
[12] "F:/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests\\BM20a2069716ead"
[13] "F:/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests\\BM20a207384b8e"
[14] "F:/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests\\BM20a20633529d"
[15] "F:/biocbuild/bbs-3.20-bioc/meat/BufferedMatrix.Rcheck/tests\\BM20a206039471d"
>
>
> ### 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: 0x00000165d07ffad0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x00000165d07ffad0>
Warning message:
In dir.create(new.directory) :
'F:\biocbuild\bbs-3.20-bioc\meat\BufferedMatrix.Rcheck\tests' already exists
>
>
> RowMode(tmp)
<pointer: 0x00000165d07ffad0>
> rowMedians(tmp)
[1] 0.400119193 0.356945619 -0.098652227 -0.132811612 -0.195725841
[6] -0.190817704 -0.462930191 0.130244141 0.118453763 0.334865540
[11] -0.123804355 0.038602536 0.512109826 0.128340570 0.129848680
[16] -0.154816484 -0.299061479 0.244186540 -0.143327460 -0.513979746
[21] -0.281481816 0.269686536 0.112300856 -0.274224729 -0.003116759
[26] 0.359627598 0.155825186 -0.210714319 -0.219818892 0.130588547
[31] 0.063226282 -0.073238474 -0.342599776 -0.214631059 -0.199032701
[36] -0.316586765 0.190454515 0.602537091 0.095032016 0.111658277
[41] 0.189484037 -0.343624317 0.069097188 0.516434762 -0.096292274
[46] -0.254949263 -0.092042412 0.151166793 0.514236309 -0.028000417
[51] -0.424211453 0.002295820 -0.002208157 -0.125608834 0.352614149
[56] 0.476758937 -0.040748949 0.569984049 0.041635058 -0.171393174
[61] -0.471935115 -0.256494444 -0.500002329 -0.113362903 0.035346849
[66] 0.311054477 0.179947691 0.534527401 0.034884973 0.225354931
[71] -0.108433893 0.475432345 0.403009751 0.017810078 -0.053823862
[76] 0.425662462 0.093437719 -0.127879440 0.387986595 -0.067343310
[81] 0.314228658 0.079322226 0.433388962 1.002029366 -0.249369492
[86] -0.304326242 -0.675894563 0.423175480 -0.297800119 0.906109502
[91] 0.260022864 0.119692605 -0.624123098 0.424234148 -0.347811058
[96] 0.014728484 0.013237418 0.110517489 -0.583398964 0.368940349
[101] 0.196575710 0.158503115 0.273817828 0.323176463 0.224800756
[106] -0.519452063 0.015015695 0.107334826 0.650965678 -0.224889820
[111] -0.127450122 -0.427700264 -0.286884260 0.224955265 -0.315980633
[116] 0.206338775 -0.213286537 0.560937902 0.035891363 0.033105608
[121] -0.199862717 -0.283172007 -0.050799608 0.369570909 -0.324598390
[126] -0.292151956 0.230115307 0.193026070 -0.274273928 0.146295226
[131] 0.464781761 0.180048629 -0.371271258 -0.019423640 0.021103963
[136] -0.123595561 -0.326356247 -0.483640193 -0.515969079 0.191822285
[141] 0.130852886 0.480994759 0.288695111 0.104026089 -0.467074023
[146] -0.044626109 0.288637367 -0.200235804 0.226640829 0.140145081
[151] 0.301738598 -0.492289512 -0.193939380 0.281207460 0.063924634
[156] 0.183627423 -0.701077693 -0.130645400 0.027573822 -0.011864571
[161] 0.022204260 -0.108626854 -0.183750592 0.078776537 0.281684912
[166] -0.312287448 0.382226964 0.285083963 0.107886832 -0.038353004
[171] 0.056537419 -0.012136676 0.463901550 -0.074162983 0.215233132
[176] -0.277874837 0.783845726 0.009541820 0.356768581 -0.207142837
[181] 0.894308928 0.013467348 0.174016077 0.069285898 0.617945132
[186] -0.365997766 -0.185335085 0.589683261 0.487365845 -0.349648399
[191] 0.318490440 0.325769628 0.361258276 -0.128331024 -0.395995077
[196] -0.075095450 -0.430662037 0.143581598 -0.213437266 -0.170308758
[201] 0.053429533 0.363593192 0.097214467 0.211557260 -0.131604096
[206] -0.059411570 -0.171823262 -0.389222087 -0.299703707 -0.125505509
[211] 0.060029772 -0.295381399 0.478713750 -0.079720450 -0.100653844
[216] 0.244653480 -0.299864239 -0.689288710 -0.006059408 0.002335893
[221] 0.114902294 -0.217226824 0.015277577 -0.075374611 0.109386921
[226] 0.165364856 -0.114352367 0.057511916 -0.030048808 0.236581647
>
> proc.time()
user system elapsed
3.82 14.51 105.51
BufferedMatrix.Rcheck/tests/rawCalltesting.Rout
R version 4.4.3 (2025-02-28 ucrt) -- "Trophy Case"
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: 0x0000019a67aff110>
> .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: 0x0000019a67aff110>
> .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: 0x0000019a67aff110>
> .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: 0x0000019a67aff110>
> 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: 0x0000019a67aff710>
> .Call("R_bm_AddColumn",P)
<pointer: 0x0000019a67aff710>
> .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: 0x0000019a67aff710>
> .Call("R_bm_AddColumn",P)
<pointer: 0x0000019a67aff710>
> .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: 0x0000019a67aff710>
> 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: 0x0000019a67aff1d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x0000019a67aff1d0>
> .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: 0x0000019a67aff1d0>
>
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x0000019a67aff1d0>
> .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: 0x0000019a67aff1d0>
>
> .Call("R_bm_RowMode",P)
<pointer: 0x0000019a67aff1d0>
> .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: 0x0000019a67aff1d0>
>
> .Call("R_bm_ColMode",P)
<pointer: 0x0000019a67aff1d0>
> .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: 0x0000019a67aff1d0>
> 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: 0x0000019a67aff230>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x0000019a67aff230>
> .Call("R_bm_AddColumn",P)
<pointer: 0x0000019a67aff230>
> .Call("R_bm_AddColumn",P)
<pointer: 0x0000019a67aff230>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFilea2201a4b7a4f" "BufferedMatrixFilea2206f8c4e28"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFilea2201a4b7a4f" "BufferedMatrixFilea2206f8c4e28"
>
>
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x0000019a67aff8f0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x0000019a67aff8f0>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x0000019a67aff8f0>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x0000019a67aff8f0>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x0000019a67aff8f0>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x0000019a67aff8f0>
> .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: 0x0000019a67affbf0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x0000019a67affbf0>
>
> .Call("R_bm_getSize",P)
[1] 10 2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x0000019a67affbf0>
>
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x0000019a67affbf0>
> 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: 0x0000019a67aff470>
> .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: 0x0000019a67aff470>
> rm(P)
>
> proc.time()
user system elapsed
0.31 0.14 0.67
BufferedMatrix.Rcheck/tests/Rcodetesting.Rout
R version 4.4.3 (2025-02-28 ucrt) -- "Trophy Case"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64
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You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
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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 0.03 0.35